DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
This action is in response to the Applicant’s filing on April 28, 2026. Claims 1-20 are pending and examined below.
Response to Arguments
The previous rejections of claims 1-20 under 35 U.S.C. 103 are withdrawn in consideration of amended independent claims 1, 8 and 20. However, new rejections of claims 1-20 under 35 U.S.C. 103 are set forth below.
Regarding claim 1, Applicant appears to be arguing that Koga does not disclose, teach or suggest “autonomously transport the refuse vehicle to a location in which the power line is not present overhead of the refuse vehicle within the threshold distance” (Applicant Remarks pg. 9). However, Koga discloses a controller that moves a refuse vehicle so that a detected obstacle, including power lines or other obstacles overhead the refuse vehicle, is no longer within a trajectory of a front-lift assembly (¶ [0076]). Koga further discloses autonomous control of a refuse vehicle (¶ [0092]) and automatically moving a refuse vehicle to avoid a detected obstacle (¶ [0099]). Thus, Koga does disclose, teach or suggest “autonomously transport the refuse vehicle to a location in which the power line is not present overhead of the refuse vehicle within the threshold distance.”
Regarding claim 8, Applicant appears to be arguing that Mahan is directed solely to a side-loading grabber assembly and does not disclose, teach or suggest “a lift apparatus comprising forks extending in a forwards direction from a front end of the refuse vehicle” (Applicant Remarks pg. 11-12). However, Mahan discloses a refuse vehicle configured as a front-loading refuse vehicle with a lift assembly including a pair of arms, coupled to the body on either side of the refuse vehicle such that the lift arms extend forward of the cab (¶ [0025] and lift assembly 200 in Fig. 1B). Mahan further discloses an attachment assembly coupled to the lift arms of the lift assembly configured to engage with a fork attachment and a refuse container that is coupled to the lift assembly by the fork attachment (¶ [0026]-[0027]). Thus, Mahan does disclose, teach or suggest “a lift apparatus comprising forks extending in a forwards direction from a front end of the refuse vehicle.”
Further, Applicant appears to be arguing that the guided forklifts of Takao are not comparable to the lift apparatus of claim 8. However, the teachings of Takao used in the rejection of claim 8 are related to determining a trajectory for a vehicle to align forks with pockets of a container based on the containers orientation. The forklift of Takao includes forks that are aligned with pockets of a pallet to allow the forklift to pick up the pallet which is comparable to the lifting apparatus of claim 8.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2021/0325529 by Koga et al. (herein after “Koga”), in view of U.S. Patent Application Publication No. US 2009/0108840 by Givens (herein after “Givens”) and WO 2023/192599 by Ghike et al. (herein after “Ghike”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 1, Koga discloses a refuse vehicle (Koga: refuse vehicle 10 in Fig. 1A), comprising:
a lift apparatus comprising forks configured to be received within pockets of a refuse container and lift and empty contents of the refuse container into a hopper of the refuse vehicle (Koga ¶ [0063]: the lift assembly 536 may include the lift assembly 40, where a fork attachment is coupled to the lift assembly 40 for engaging and lifting front loading the refuse containers 60 (e.g., industrial or commercial refuse cans, as shown in FIG. 1A));
an electromagnetic radiation (“EMR”) detector (Koga ¶ [0045]: The sensor(s) 422 may include any type of device that is configured to capture data associated with the detection of objects such as refuse containers and/or pedestrians. The sensor(s) 422 includes any one and/or a combination of proximity sensors, infrared sensors, electromagnetic sensors, capacitive sensors, photoelectric sensors, inductive sensors, radar, ultrasonic sensors, Hall Effect sensors, fiber optic sensors, Doppler Effect sensors, magnetic sensors, laser sensors (e.g., LIDAR sensors), sonar, and/or the like)
processing circuitry (Koga: controller 500 in Fig. 5) configured to:
obtain feedback from the (Koga ¶ [0070]: The sensor(s) 612 collect data that may indicate the presence of obstacles around the refuse vehicle 10 and send the data to the controller);
determine, based on the feedback, whether the power line is present overhead of the refuse vehicle within a threshold distance above the refuse vehicle (Koga ¶ [0074]: Scenario 1100 illustrates a refuse vehicle 10 underneath an obstacle shown as power lines 1120; Koga ¶ [0076]: the controller is configured to detect the power lines 1120 within the path of trajectory 1430. For example, the controller may detect power lines 1120 within the trajectory 1430 of refuse container 60 and front-lift assembly 40 of the refuse vehicle 10; power lines 1120 in Fig. 11); and
prevent operation of the lift apparatus responsive to determining that the power line is present within the threshold distance above the refuse vehicle (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120); and
responsive to determining that the power line is present within the threshold distance above the refuse vehicle, and based on positions of detected obstacles (Koga ¶ [0098]: At step 1610, the controller determines the position of an obstacle) (Koga ¶ [0099]: At step 1612, a response is initiated based on the detection and/or classification of an obstacle. The response may include any number of automated control actions. For example, the response may include presenting a notification or alert of a detected pedestrian in a blind spot to an operator via a user interface (e.g., user interface 420). As another example, the control action(s) may include automatically moving the refuse vehicle and/or systems of the refuse vehicle to avoid the obstacle; Koga ¶ [0076]: the controller moves the refuse vehicle 10 so that the detected obstacle is no longer within the trajectory of front-lift assembly 40; Koga ¶ [0092]: As illustrated in FIG. 15B, the controller may detect obstacles surrounding the refuse vehicle 10 and plot a path, shown as path 1544 towards refuse container 1590 … the controller may direct the refuse vehicle 10 along path 1544 until the refuse vehicle 10 is at a desired distance to refuse container 1590. In some embodiments, the controller directs the refuse vehicle 10 along path 1544 in an autonomous operation (e.g., where the refuse vehicle 10 is autonomous) in order to reduce or eliminate operator input).
It is noted that Koga discloses electromagnetic sensors and overhead power line detection using sensors but does not explicitly disclose an electromagnetic radiation (“EMR”) detector configured to detect a presence of a power line overhead of the refuse vehicle. Further, it is noted that Koga discloses determining positions of detected obstacles, including overhead obstacles, relative to a refuse vehicle and autonomously controlling the refuse vehicle to avoid the detected obstacles but does not explicitly disclose a profile of a jobsite.
However, Givens, in the same field of endeavor, teaches an electromagnetic radiation (“EMR”) detector configured to detect a presence of a power line overhead of the refuse vehicle (Givens ¶ [0023]: FIG. 3 is an illustrative diagram of one embodiment of a wireless sensor (300) configured to sense the electromagnetic signature of a power line (130, FIG. 1); Givens ¶ [0028]: According to one exemplary embodiment, the variation in the antenna geometries gives each sub sensor (comprised of an antenna/electronics pair) a varying sensitivity to an electromagnetic field. As the boom (130) approaches a power line, the sensor (300) passes into the electromagnetic field generated by the passage of current through the power line (150). According to the exemplary configuration, the first sub sensor (305, 330) is the most efficient at sensing the electromagnetic field and converting the electromagnetic field into energy. This energy powers the electronics segment (330) which transmits its wireless signal to the base station).
Further, Ghike, in the same field of endeavor, teaches based on a profile of a jobsite, autonomously transport the refuse vehicle to a location (Ghike ¶ [0015]: the systems, methods, and apparatuses described herein provide a technical solution to the technical problem of autonomous vehicle route planning by providing an improved, centralized maps to each of the vehicles in a fleet, in real-time or near real-time, such that each of the vehicles uses the most up-to-date map available for route planning to improve autonomous operation (e.g., avoid collisions with obstacles); Ghike ¶ [0026]: The map data 134 may also include the location of one or more components of the machinery 190, obstacles that may block a vehicle from moving along a road or path, and/or other information related to generating a map of the predetermined location. In some embodiments, the map data 134 may include sensor data detected by one or more sensors, such as the vehicle sensors 385 shown in FIG. 2, and/or other sensors associated with the predetermined location. The sensor data may include three-dimensional image data that depicts the location of the roads, paths, machinery components, obstacles, and/or other objects within the predetermined location. In some embodiments, the map data 134 may be used to generate a map of the predetermined area (e.g., by the map generation circuit 142). The map may be used to enable the vehicles 202 to autonomously navigate the predetermined area).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting overhead powerlines to prevent a lifting operation and autonomously move away from the powerlines of Koga to include the electromagnetic sensors of Givens and the obstacle map for autonomous vehicle route planning of Ghike with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to sense proximity of mobile equipment relative to power lines and to prevent contact by the equipment with the power line (Givens ¶ [0006]) and to improve autonomous vehicle operation and obstacle avoidance by providing the most up-to-date obstacle maps to a vehicle in a fleet (Ghike ¶ [0015]).
Regarding claim 2, the combination of Koga, Givens and Ghike discloses wherein the processing circuitry is configured to determine a relative distance between the power line and a top of the refuse vehicle (Kago ¶ [0075]: the user interface displays a distance between the refuse vehicle 10 and power lines 1120. The distance may be displayed numerically. In some embodiments, the user interface displays the distance graphically with a digital representation of the refuse vehicle 10 and power lines 1120) based on an intensity of EMR detected by the EMR detector (Givens ¶ [0028]: According to one exemplary embodiment, the variation in the antenna geometries gives each sub sensor (comprised of an antenna/electronics pair) a varying sensitivity to an electromagnetic field. As the boom (130) approaches a power line, the sensor (300) passes into the electromagnetic field generated by the passage of current through the power line (150). According to the exemplary configuration, the first sub sensor (305, 330) is the most efficient at sensing the electromagnetic field and converting the electromagnetic field into energy).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting overhead powerlines to prevent a lifting operation and autonomously move away from the powerlines of Koga modified by the electromagnetic sensors of Givens and the obstacle map for autonomous vehicle route planning of Ghike to further include the antenna sub sensor geometries with varying sensitivity to electromagnetic fields of Givens with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to sense proximity of mobile equipment relative to power lines and to prevent contact by the equipment with the power line (Givens ¶ [0006]).
Regarding claim 3, the combination of Koga, Givens and Ghike discloses wherein the refuse vehicle further comprises:
a distance sensor (Koga ¶ [0045]: Data captured by the sensor(s) 422 may include, for example, raw image data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.) that may be used to detect objects. For example, the sensor(s) 422 may include a camera and/or software component configured to determine a distance to obstacles identified in images from the camera) disposed on a top of the refuse vehicle, the distance sensor configured to detect a relative distance of an obstacle that is overhead of the refuse vehicle (Koga ¶ [0072]: In some embodiments, the distance is calculated by the controller using data provided by the sensor(s) 1010 and machine learning techniques; Koga ¶ [0084]: scenario 1300 illustrates the refuse vehicle 10 underneath a barrier, shown as barrier 1330. Barrier 1330 may be a parking structure, overhang, bridge, bypass, or any other obstacle that may be above the refuse vehicle 10. In scenario 1300 the refuse vehicle 10 is traveling along direction 1340 towards and under barrier 1330. In some embodiments, barrier 1330 is located in a blind spot that is an area that cannot be seen by an operator of the refuse vehicle 10. In some embodiments, the sensor(s) 1210 are positioned on the top of the refuse vehicle 10. For example, the sensor(s) 1210 may be placed on top of the refuse vehicle 10 at the front and rear of the vehicle and detect obstacles);
wherein the processing circuitry is configured to prevent operation of the lift apparatus responsive to determining that the obstacle is within the threshold distance above the refuse vehicle (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120; Koga ¶ [0085]: the sensor(s) 1210 detect barrier 1330 and the controller initiates a control action when barrier 1330 enters safety zone 1320. In some embodiments, the control action includes generating an alert to the operator of the refuse vehicle 10 indicating the presence of obstacles 908 above the refuse vehicle 10. In some embodiments, the control action additionally and/or alternatively includes controlling an aspect of the refuse vehicle 10. For example, the control action may include limiting the movement of the refuse vehicle 10 so as to prevent it from coming into contact with barrier 1330).
Regarding claim 4, the combination of Koga, Givens and Ghike discloses wherein the refuse vehicle further comprises:
a camera (Koga ¶ [0045]: Data captured by the sensor(s) 422 may include, for example, raw image data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.) that may be used to detect objects. For example, the sensor(s) 422 may include a camera and/or software component configured to determine a distance to obstacles identified in images from the camera) disposed on a top of the refuse vehicle, the camera configured to detect a relative distance of an obstacle that is overhead of the refuse vehicle (Koga ¶ [0072]: In some embodiments, the distance is calculated by the controller using data provided by the sensor(s) 1010 and machine learning techniques; Koga ¶ [0084]: scenario 1300 illustrates the refuse vehicle 10 underneath a barrier, shown as barrier 1330. Barrier 1330 may be a parking structure, overhang, bridge, bypass, or any other obstacle that may be above the refuse vehicle 10. In scenario 1300 the refuse vehicle 10 is traveling along direction 1340 towards and under barrier 1330. In some embodiments, barrier 1330 is located in a blind spot that is an area that cannot be seen by an operator of the refuse vehicle 10. In some embodiments, the sensor(s) 1210 are positioned on the top of the refuse vehicle 10. For example, the sensor(s) 1210 may be placed on top of the refuse vehicle 10 at the front and rear of the vehicle and detect obstacles);
wherein the processing circuitry is configured to prevent operation of the lift apparatus responsive to determining that the obstacle is within the threshold distance above the refuse vehicle (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120; Koga ¶ [0085]: the sensor(s) 1210 detect barrier 1330 and the controller initiates a control action when barrier 1330 enters safety zone 1320. In some embodiments, the control action includes generating an alert to the operator of the refuse vehicle 10 indicating the presence of obstacles 908 above the refuse vehicle 10. In some embodiments, the control action additionally and/or alternatively includes controlling an aspect of the refuse vehicle 10. For example, the control action may include limiting the movement of the refuse vehicle 10 so as to prevent it from coming into contact with barrier 1330).
Regarding claim 5, the combination of Koga, Givens and Ghike discloses further comprising an EMR detector (Givens ¶ [0023]: FIG. 3 is an illustrative diagram of one embodiment of a wireless sensor (300) configured to sense the electromagnetic signature of a power line (130, FIG. 1); Givens ¶ [0028]: According to one exemplary embodiment, the variation in the antenna geometries gives each sub sensor (comprised of an antenna/electronics pair) a varying sensitivity to an electromagnetic field. As the boom (130) approaches a power line, the sensor (300) passes into the electromagnetic field generated by the passage of current through the power line (150). According to the exemplary configuration, the first sub sensor (305, 330) is the most efficient at sensing the electromagnetic field and converting the electromagnetic field into energy. This energy powers the electronics segment (330) which transmits its wireless signal to the base station) disposed on a lift arm of the lift apparatus (Koga: sensor 1110 in Fig. 11 and sensor 1410 in Fig. 14 positioned on the arm of the lift apparatus; Koga ¶ [0046]: The sensor(s) 422 may be disposed at any number of locations throughout and/or around the refuse vehicle 10 for capturing image and/or object data from any direction with respect to the refuse vehicle 10 … In some embodiments, one or more of sensor(s) 422 may be located on an attachment utilized by the refuse vehicle 10, such as container attachment 60 described above. It should be understood that sensor(s) may be positioned anywhere on the refuse vehicle 10), the EMR detector configured to detect a relative distance between the power line and the lift arm of the lift apparatus (Kago ¶ [0075]: the user interface displays a distance between the refuse vehicle 10 and power lines 1120. The distance may be displayed numerically. In some embodiments, the user interface displays the distance graphically with a digital representation of the refuse vehicle 10 and power lines 1120), wherein the processing circuitry is configured to limit further operation of the lift apparatus in response to detecting that the power line is within a threshold distance of the lift arm (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120).
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Regarding claim 6, the combination of Koga, Givens and Ghike discloses further comprising a distance sensor (Koga ¶ [0045]: Data captured by the sensor(s) 422 may include, for example, raw image data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.) that may be used to detect objects. For example, the sensor(s) 422 may include a camera and/or software component configured to determine a distance to obstacles identified in images from the camera) disposed on a lift arm of the lift apparatus (Koga: sensor 1110 in Fig. 11 and sensor 1410 in Fig. 14 positioned on the arm of the lift apparatus; Koga ¶ [0046]: The sensor(s) 422 may be disposed at any number of locations throughout and/or around the refuse vehicle 10 for capturing image and/or object data from any direction with respect to the refuse vehicle 10 … In some embodiments, one or more of sensor(s) 422 may be located on an attachment utilized by the refuse vehicle 10, such as container attachment 60 described above. It should be understood that sensor(s) may be positioned anywhere on the refuse vehicle 10), the distance sensor configured to detect a relative distance between an obstacle and the lift arm of the lift apparatus, wherein the processing circuitry is configured to limit further operation of the lift apparatus in response to detecting that the obstacle is within a threshold distance of the lift arm (Koga ¶ [0072]: the controller may not allow an operator of the refuse vehicle 10 to operate the side-lift assembly 1020 within a set distance of the barrier 1030. The distance may be based off of dimensions of the refuse vehicle 10 and/or the side-lift assembly 1020. In some embodiments, the distance may be a default minimum distance. In some embodiments, an operator sets the distance. In some embodiments, the distance is calculated by the controller using data provided by the sensor(s) 1010 and machine learning techniques).
Regarding claim 7, the combination of Koga, Givens and Ghike discloses further comprising a camera (Koga ¶ [0045]: Data captured by the sensor(s) 422 may include, for example, raw image data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.) that may be used to detect objects. For example, the sensor(s) 422 may include a camera and/or software component configured to determine a distance to obstacles identified in images from the camera) disposed on a lift arm of the lift apparatus (Koga: sensor 1110 in Fig. 11 and sensor 1410 in Fig. 14 positioned on the arm of the lift apparatus; Koga ¶ [0046]: The sensor(s) 422 may be disposed at any number of locations throughout and/or around the refuse vehicle 10 for capturing image and/or object data from any direction with respect to the refuse vehicle 10 … In some embodiments, one or more of sensor(s) 422 may be located on an attachment utilized by the refuse vehicle 10, such as container attachment 60 described above. It should be understood that sensor(s) may be positioned anywhere on the refuse vehicle 10), the camera configured to detect a relative distance between an obstacle and the lift arm of the lift apparatus, wherein the processing circuitry is configured to limit further operation of the lift apparatus in response to detecting that the obstacle is within a threshold distance of the lift arm (Koga ¶ [0072]: the controller may not allow an operator of the refuse vehicle 10 to operate the side-lift assembly 1020 within a set distance of the barrier 1030. The distance may be based off of dimensions of the refuse vehicle 10 and/or the side-lift assembly 1020. In some embodiments, the distance may be a default minimum distance. In some embodiments, an operator sets the distance. In some embodiments, the distance is calculated by the controller using data provided by the sensor(s) 1010 and machine learning techniques).
Claims 8-14, 16-17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2021/0292086 by Mahan et al. (herein after “Mahan”), in view of U.S. Patent Application Publication No. US 2020/0339347 by Williams et al. (herein after “Williams”), WO 2021/171974 by Takao (herein after “Takao”) and U.S. Patent Application Publication No. US 2021/0325529 by Koga et al. (herein after “Koga”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 8, Mahan discloses a refuse vehicle (Mahan: refuse vehicle 10 in Fig. 1B), comprising:
a lift apparatus comprising forks extending in a forwards direction from a front end of the refuse vehicle (Mahan ¶ [0025]: Lift assembly 200 includes a pair of arms, shown as lift arms 52, coupled to the frame 12 and/or the body 14 on either side of the refuse vehicle 10 such that the lift arms 52 extend forward of the cab 16 (e.g., a front-loading refuse vehicle, etc.); Mahan ¶ [0026]: attachment assembly 210 may be configured to engage with a second attachment, such as a fork attachment, to selectively and releasably secure second attachment to the lift assembly 200), configured to (Mahan ¶ [0027]: Such articulation may assist in tipping refuse out of the container attachment 220 and/or a refuse container (e.g., coupled to the lift assembly 200 by a fork attachment, etc.) and into the hopper volume of the refuse compartment 30 through an opening in the cover 36);
an outwards facing camera configured to obtain image data of an area proximate the refuse vehicle (Mahan ¶ [0033]: Controller 400 may be configured to receive data from image and/or object sensors (i.e., cameras and sensors) to detect and/or track a plurality of refuse can located on any side of a refuse vehicle (e.g., the front, sides, or rear of refuse vehicle 10)); and
processing circuitry (Mahan: controller 400 in Fig. 4) configured to:
detect, based on the image data, a presence, location, (Mahan ¶ [0045]: Object detector 420 may generally receive and process data from image/object sensors 430 to detect objects (e.g., refuse cans). It will be appreciated that, has denoted herein, the data received and process by object detector 420 may include any type of data as described above with respect to image/object sensors 430, including video from which images and/or other image data can be extracted. As described above, the data may also include data from one or more sensors (e.g., LIDAR, radar, etc.) that may be utilized to detect an object (e.g., a refuse can) and/or a location or position of the object);
determine, based on the presence, location, (Mahan ¶ [0076]: At step 906, a trajectory is generated for the refuse vehicle based on the location of the refuse can. Simultaneously, at step 908, a trajectory is generated for an actuator assembly of the refuse vehicle. The trajectories for the refuse vehicle and actuator assembly may indicate a path that the corresponding systems follow to reach and engage the refuse can. The trajectory of the refuse vehicle, for example, may indicate a path or a set of movements for the refuse vehicle to follow to move next to the refuse can so that the actuator assembly may move to engage the refuse can. Similarly, the trajectory of the actuator assembly may indicate a path or a set of movements that the actuator assembly may follow to engage the refuse can once the refuse vehicle has moved alongside the refuse can);
at least one of (i) autonomously operate the refuse vehicle to transport along the first path, or (ii) operate a display screen to provide the image data with a visual indication of the first path superimposed over the image data (Mahan ¶ [0077]: At steps 910 and 912, the refuse vehicle and actuator assembly navigate (i.e., move) to the refuse can. In autonomous and/or semi-autonomous operations, the refuse vehicle (e.g., refuse vehicle 10) and actuator assembly (e.g., actuator assembly 436) may be controlled or commanded (e.g., by control module 424) to automatically navigate to the refuse can. For example, the refuse vehicle may automatically move to the refuse can, and the actuator may automatically move to engage the refuse can, without operator input. In other embodiments, the trajectories generated at steps 906 and 908 may be presented to the operator (e.g., via a user interface) so that the operator may navigate the refuse vehicle and/or the actuator to the refuse can. As an example, the trajectories may be presented via a user interface, indicating a path and/or movements that the operator should follow to navigate to the refuse can);
.
It is noted Mahan discloses a system and method for detecting refuse containers, determining trajectories for a refuse vehicle to approach to engage refuse containers and autonomously controlling a refuse vehicle along the trajectories or displaying the trajectories to an operator but fails to explicitly disclose forks configured to be received within pockets of a refuse container;
detect, based on the image data, an orientation of a refuse container;
determine, based on the orientation of the refuse container, a first path for transportation of the refuse vehicle such that transportation of the refuse vehicle along the first path results in the forks of the lift apparatus being properly aligned with and inserted into the pockets of the refuse container; and
determine, based on presence and location of overhead obstacles, a second path to a location with sufficient overhead clearance above the refuse vehicle for operation of the lift apparatus; and
at least one of (i) autonomously operate the refuse vehicle to transport along the second path, or (ii) operate the display screen to provide the image data with a visual indication of the second path superimposed over the image data.
However, Williams, in the same field of endeavor, teaches forks extending in a forwards direction from a front end of the refuse vehicle (Williams: fork assembly 113 in Figs. 2-3D), configured to be received within pockets of a refuse container and lift and empty contents of the refuse container into a hopper of the refuse vehicle (Williams ¶ [0005]: a refuse collection vehicle includes a fork assembly that is operable to engage one or more fork pockets of a refuse container, a lift arm that is operable to lift a refuse container);
processing circuitry (Williams: onboard computing device 112 in Fig. 1) configured to:
detect, based on the image data, a presence, location, and orientation of a refuse container (Williams ¶ [0045]: The data captured by sensor 160 can be further processed by the onboard computing device 112 to determine the location of various components of the detected refuse container 130. In some implementations, a computing device 112 receives images or video captured by the sensor 160 and uses machine learning based image processing techniques to determine the position of one or more fork pockets 180 on a refuse container 130. In some implementations, images captured by the sensor 160 are processed by a computing device 112 to detect the sides of one or more fork pockets 180 to determine one or more dimensions of each of the fork pockets 180, such as the height and width of each of the fork pockets 180. In some examples, a computing device can process images provided by sensor 160 to determine a location of one or more corners of the one or more fork pockets 180 of a detected refuse container 130. The detected corners of the fork pockets 180 can be provided as GPS coordinates, and based on these coordinates, the height and angular position of the fork pockets 180 relative to the surface 190 on which the vehicle 102 is positioned can be determined; refuse container positions and orientations in Figs. 3A-3D);
determine, based on the presence, location, and orientation of the refuse container, a first path that results in the forks of the lift apparatus being properly aligned with and inserted into the pockets of the refuse container (Williams ¶ [0049]: Upon receiving data describing the position of one or more fork pockets 180 of a refuse container 130 proximate the vehicle 102 collected by one or more container detection sensors 160, the position of the lift arm 111 and the fork assembly 113 of the vehicle 102 can be automatically adjusted to engage the detected refuse container 130. For example, the position of the lift arm 111 and the fork assembly 113 of the vehicle 102 can be automatically adjusted to align one or more ends 126 of the forks 116 of the fork assembly 113 with the detected fork pockets 180 of the detected refuse container 130).
Further, Takao, in a similar field of endeavor, teaches detect, based on the image data, a presence, location, and orientation of a (Takao ¶ [0032]: The target object information acquisition unit 74 illustrated in FIG. 5 acquires the detection result of the position information of the pallet P that is the target object from the sensor 26 of the mobile object 10 at the start positionAR1. The position information of the pallet P is information indicating the orientation of the pallet P, and more specifically, information indicating the position and orientation of the pallet P);
determine, based on the presence, location, and orientation of the (Takao ¶ [0104]: The control device 28 sets the trajectory TR1 to the target position posture AR2 on the basis of the detection result of the position and posture of the pallet P by the sensor 26 of the moving body 10. A method of setting the trajectory TR1 will be described later. The control device 28 moves the moving body 10 along the trajectory TR1 to the target position and orientation AR2, and causes the moving body 10 to pick up the pallet P; route R and trajectory TR1 in Fig. 30).
Examiner interprets the combination of Mahan, Williams and Takao to teach a refuse vehicle capable of determining a trajectory for a refuse vehicle and lift assembly that will result in forks of the lift assembly being aligned and inserted into pockets of a refuse container. Mahan discloses a system and method for determining a trajectory for a refuse vehicle and a trajectory for a lift assembly to engage a refuse container. Mahan is not specific to a refuse container with pockets or aligning forks with pockets of a refuse container. However, Williams teaches determining movements for a lift assembly to align forks of the lift assembly with pockets of a refuse container. Takao teaches a system for determining a vehicle trajectory to align forks with pockets of a container based on container orientation. Thus, combining the teachings of Mahan, Williams and Takao would predictably result in a system that determines a trajectory for a refuse vehicle to move to a refuse container and simultaneously determines a trajectory for a lift assembly to align forks with pockets of the refuse container.
Finally, Koga, in the same field of endeavor, teaches determine, based on presence and location of overhead obstacles (Koga ¶ [0074]: Scenario 1100 illustrates a refuse vehicle 10 underneath an obstacle shown as power lines 1120; Koga ¶ [0076]: the controller is configured to detect the power lines 1120 within the path of trajectory 1430. For example, the controller may detect power lines 1120 within the trajectory 1430 of refuse container 60 and front-lift assembly 40 of the refuse vehicle 10; power lines 1120 in Fig. 11), a second path to a location with sufficient overhead clearance above the refuse vehicle for operation of the lift apparatus (Koga ¶ [0099]: At step 1612, a response is initiated based on the detection and/or classification of an obstacle. The response may include any number of automated control actions. For example, the response may include presenting a notification or alert of a detected pedestrian in a blind spot to an operator via a user interface (e.g., user interface 420). As another example, the control action(s) may include automatically moving the refuse vehicle and/or systems of the refuse vehicle to avoid the obstacle; Koga ¶ [0076]: the controller moves the refuse vehicle 10 so that the detected obstacle is no longer within the trajectory of front-lift assembly 40; Koga ¶ [0092]: As illustrated in FIG. 15B, the controller may detect obstacles surrounding the refuse vehicle 10 and plot a path, shown as path 1544 towards refuse container 1590 … the controller may direct the refuse vehicle 10 along path 1544 until the refuse vehicle 10 is at a desired distance to refuse container 1590. In some embodiments, the controller directs the refuse vehicle 10 along path 1544 in an autonomous operation (e.g., where the refuse vehicle 10 is autonomous) in order to reduce or eliminate operator input); and
at least one of (i) autonomously operate the refuse vehicle to transport along the second path, or (ii) operate the display screen to provide the image data with a visual indication of the second path superimposed over the image data (Koga ¶ [0099]: the control action(s) may include automatically moving the refuse vehicle and/or systems of the refuse vehicle to avoid the obstacle; Koga ¶ [0076]: the controller moves the refuse vehicle 10 so that the detected obstacle is no longer within the trajectory of front-lift assembly 40; Koga ¶ [0092]: As illustrated in FIG. 15B, the controller may detect obstacles surrounding the refuse vehicle 10 and plot a path, shown as path 1544 towards refuse container 1590 … the controller may direct the refuse vehicle 10 along path 1544 until the refuse vehicle 10 is at a desired distance to refuse container 1590. In some embodiments, the controller directs the refuse vehicle 10 along path 1544 in an autonomous operation (e.g., where the refuse vehicle 10 is autonomous) in order to reduce or eliminate operator input).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan to include the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to increase waste collection efficiency and reduce operator error in refuse collection (Williams ¶ [0015]), to reduce the calculation load of a trajectory in a moving body that automatically moves (Takao ¶ [0010]), and to allow a refuse vehicle to avoid detected obstacles (Koga ¶ [0076]).
Regarding claim 9, the combination of Mahan, Williams, Takao, and Koga discloses wherein the at least one of the first path and the second path for transportation of the refuse vehicle comprise a reverse path for the refuse vehicle, a forwards path for the refuse vehicle, and a transition between the reverse path and the forwards path, the transition between the reverse path and the forwards path (Takao: route R, trajectories TR1 and TR2 in Fig. 30) indicating a point at which to transition a transmission of the refuse vehicle between a reverse gear and a forwards gear (Mahan ¶ [0043]: a transmission control unit (TCU); Examiner interprets the refuse vehicle of Mahan to implicitly include a transmission for engaging different gears including a forward and reverse gear).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to further include the route including a forward and reverse path and a transition point of Takao with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to reduce the calculation load of a trajectory in a moving body that automatically moves (Takao ¶ [0010]).
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Regarding claim 10, the combination of Mahan, Williams, Takao, and Koga discloses wherein the processing circuitry is configured to determine, based on the image data, a location of the pockets of the refuse container (Williams ¶ [0045]: The data captured by sensor 160 can be further processed by the onboard computing device 112 to determine the location of various components of the detected refuse container 130. In some implementations, a computing device 112 receives images or video captured by the sensor 160 and uses machine learning based image processing techniques to determine the position of one or more fork pockets 180 on a refuse container 130. In some implementations, images captured by the sensor 160 are processed by a computing device 112 to detect the sides of one or more fork pockets 180 to determine one or more dimensions of each of the fork pockets 180, such as the height and width of each of the fork pockets 180. In some examples, a computing device can process images provided by sensor 160 to determine a location of one or more corners of the one or more fork pockets 180 of a detected refuse container 130. The detected corners of the fork pockets 180 can be provided as GPS coordinates, and based on these coordinates, the height and angular position of the fork pockets 180 relative to the surface 190 on which the vehicle 102 is positioned can be determined; refuse container positions and orientations in Figs. 3A-3D), the first path determined based on the location of the pockets of the refuse container such that the forks of the lift apparatus are aligned with and inserted into the pockets as the refuse vehicle travels along the first path towards the refuse container (Mahan ¶ [0076]: At step 906, a trajectory is generated for the refuse vehicle based on the location of the refuse can. Simultaneously, at step 908, a trajectory is generated for an actuator assembly of the refuse vehicle. The trajectories for the refuse vehicle and actuator assembly may indicate a path that the corresponding systems follow to reach and engage the refuse can; Williams ¶ [0049]: Upon receiving data describing the position of one or more fork pockets 180 of a refuse container 130 proximate the vehicle 102 collected by one or more container detection sensors 160, the position of the lift arm 111 and the fork assembly 113 of the vehicle 102 can be automatically adjusted to engage the detected refuse container 130; Takao ¶ [0038]: The trajectory setting unit 80 (see FIG. 5) sets the trajectory TR from the start position AR1 (the moving body 10 at the start position AR1) to the target position posture AR2. The trajectory setting unit 80 sets the target position posture AR2 on the basis of the position information of the pallet P acquired by the target object information acquisition unit 74, that is, based on the position and orientation of the pallet P. That is, the pallet P can be picked up from the position and orientation of the pallet P (straight traveling to insert the fork 24 into the opening Pb of the pallet P), and the position and the posture are calculated to be the target position and posture AR2).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to explicitly include the fork pocket detection and fork assembly alignment of Williams and the determination of a trajectory that aligns forks with container pockets of Takao with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to increase waste collection efficiency and reduce operator error in refuse collection (Williams ¶ [0015]) and reduce the calculation load of a trajectory in a moving body that automatically moves (Takao ¶ [0010]).
Regarding claim 11, the combination of Mahan, Williams, Takao, and Koga discloses wherein the processing circuitry is configured to determine, based on the presence, location, and orientation of the refuse container (Mahan ¶ [0045]: Object detector 420 may generally receive and process data from image/object sensors 430 to detect objects (e.g., refuse cans). It will be appreciated that, has denoted herein, the data received and process by object detector 420 may include any type of data as described above with respect to image/object sensors 430, including video from which images and/or other image data can be extracted. As described above, the data may also include data from one or more sensors (e.g., LIDAR, radar, etc.) that may be utilized to detect an object (e.g., a refuse can) and/or a location or position of the object; Takao ¶ [0032]: The target object information acquisition unit 74 illustrated in FIG. 5 acquires the detection result of the position information of the pallet P that is the target object from the sensor 26 of the mobile object 10 at the start position AR1. The position information of the pallet P is information indicating the orientation of the pallet P, and more specifically, information indicating the position and orientation of the pallet P), a location of the pockets of the refuse container (Williams ¶ [0045]: The data captured by sensor 160 can be further processed by the onboard computing device 112 to determine the location of various components of the detected refuse container 130. In some implementations, a computing device 112 receives images or video captured by the sensor 160 and uses machine learning based image processing techniques to determine the position of one or more fork pockets 180 on a refuse container 130. In some implementations, images captured by the sensor 160 are processed by a computing device 112 to detect the sides of one or more fork pockets 180 to determine one or more dimensions of each of the fork pockets 180, such as the height and width of each of the fork pockets 180. In some examples, a computing device can process images provided by sensor 160 to determine a location of one or more corners of the one or more fork pockets 180 of a detected refuse container 130. The detected corners of the fork pockets 180 can be provided as GPS coordinates, and based on these coordinates, the height and angular position of the fork pockets 180 relative to the surface 190 on which the vehicle 102 is positioned can be determined; refuse container positions and orientations in Figs. 3A-3D), the first path determined based on the location of the pockets of the refuse container such that the forks of the lift apparatus are aligned with and inserted into the pockets as the refuse vehicle travels along the first path towards the refuse container (Mahan ¶ [0076]: At step 906, a trajectory is generated for the refuse vehicle based on the location of the refuse can. Simultaneously, at step 908, a trajectory is generated for an actuator assembly of the refuse vehicle. The trajectories for the refuse vehicle and actuator assembly may indicate a path that the corresponding systems follow to reach and engage the refuse can; Williams ¶ [0049]: Upon receiving data describing the position of one or more fork pockets 180 of a refuse container 130 proximate the vehicle 102 collected by one or more container detection sensors 160, the position of the lift arm 111 and the fork assembly 113 of the vehicle 102 can be automatically adjusted to engage the detected refuse container 130; Takao ¶ [0038]: The trajectory setting unit 80 (see FIG. 5) sets the trajectory TR from the start position AR1 (the moving body 10 at the start position AR1) to the target position posture AR2. The trajectory setting unit 80 sets the target position posture AR2 on the basis of the position information of the pallet P acquired by the target object information acquisition unit 74, that is, based on the position and orientation of the pallet P. That is, the pallet P can be picked up from the position and orientation of the pallet P (straight traveling to insert the fork 24 into the opening Pb of the pallet P), and the position and the posture are calculated to be the target position and posture AR2).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to explicitly include the fork pocket detection and fork assembly alignment of Williams and the determination of a trajectory that aligns forks with container pockets of Takao with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to increase waste collection efficiency and reduce operator error in refuse collection (Williams ¶ [0015]) and reduce the calculation load of a trajectory in a moving body that automatically moves (Takao ¶ [0010]).
Regarding claim 12, the combination of Mahan, Williams, Takao, and Koga discloses wherein the first path is determined from a current location of the refuse vehicle to the refuse container (Mahan ¶ [0075]: At step 904, a location of the identified refuse can is determined. In some embodiments, the location of the refuse can may be determined based on the location of the refuse vehicle, such that the location of the refuse can is determined relative to the refuse vehicle; Mahan ¶ [0076]: At step 906, a trajectory is generated for the refuse vehicle based on the location of the refuse can).
Regarding claim 13, the combination of Mahan, Williams, Takao, and Koga wherein the first path is determined based on a current position and orientation of the refuse vehicle relative to the refuse container (Mahan ¶ [0075]: At step 904, a location of the identified refuse can is determined. In some embodiments, the location of the refuse can may be determined based on the location of the refuse vehicle, such that the location of the refuse can is determined relative to the refuse vehicle; Takao ¶ [0038]: The trajectory setting unit 80 (see FIG. 5) sets the trajectory TR from the start position AR1 (the moving body 10 at the start position AR1) to the target position posture AR2. The trajectory setting unit 80 sets the target position posture AR2 on the basis of the position information of the pallet P acquired by the target object information acquisition unit 74, that is, based on the position and orientation of the pallet P. That is, the pallet P can be picked up from the position and orientation of the pallet P (straight traveling to insert the fork 24 into the opening Pb of the pallet P), and the position and the posture are calculated to be the target position and posture AR2), a turning radius of the refuse vehicle, and a size of the refuse vehicle (Takao ¶ [0024]: In addition to the map information of the facility W, the route R may be set based on the information of the vehicle specification of the moving body 10. The information of the vehicle specification is, for example, a specification that affects a path on which the moving body 0 can move, such as a size and a minimum turning radius of the moving body 0).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to explicitly include the determination of a trajectory based on a pose, size and turning radius of a mobile body of Takao with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to reduce the calculation load of a trajectory in a moving body that automatically moves (Takao ¶ [0010]).
Regarding claim 14, the combination of Mahan, Williams, Takao, and Koga discloses wherein the processing circuitry is configured to determine a plurality of first paths based on detection of a plurality of refuse containers (Mahan ¶ [0073]: At step 902, a particular refuse can is identified. As described above, multiple objects including multiple refuse cans may be detected. In order to initiate a control action, a particular refuse can may be identified, either automatically or based on a user input. In the first case, where a particular refuse can is automatically identified in order to initiate a control action, a controller (e.g., controller 400) may implement a number of parameters for identifying the particular refuse can. For example, the refuse can may be identified based on identifying features (e.g., size, color, shape, logos or markings, etc.) or may be selected based on its proximity to the refuse vehicle (e.g., the closest refuse can may be identified first). The particular refuse can may be automatically identified in autonomous operations (e.g., where refuse vehicle 10 is autonomous) in order to reduce or eliminate operator input). Examiner interprets the system of Mahan to include detection of multiple refuse containers. In instances where multiple refuse containers are detected process 900 in Fig. 9 determines trajectories for approaching and engaging each refuse container in an order that is based on a desired selection criterion.
Regarding claim 16, the combination of Mahan, Williams, Takao, and Koga discloses further comprising:
a distance sensor (Koga ¶ [0045]: Data captured by the sensor(s) 422 may include, for example, raw image data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.) that may be used to detect objects. For example, the sensor(s) 422 may include a camera and/or software component configured to determine a distance to obstacles identified in images from the camera) disposed on a top of the refuse vehicle, the distance sensor configured to detect a relative distance of an obstacle that is overhead of the refuse vehicle (Koga ¶ [0072]: In some embodiments, the distance is calculated by the controller using data provided by the sensor(s) 1010 and machine learning techniques; Koga ¶ [0084]: scenario 1300 illustrates the refuse vehicle 10 underneath a barrier, shown as barrier 1330. Barrier 1330 may be a parking structure, overhang, bridge, bypass, or any other obstacle that may be above the refuse vehicle 10. In scenario 1300 the refuse vehicle 10 is traveling along direction 1340 towards and under barrier 1330. In some embodiments, barrier 1330 is located in a blind spot that is an area that cannot be seen by an operator of the refuse vehicle 10. In some embodiments, the sensor(s) 1210 are positioned on the top of the refuse vehicle 10. For example, the sensor(s) 1210 may be placed on top of the refuse vehicle 10 at the front and rear of the vehicle and detect obstacles);
wherein the processing circuitry is configured to prevent operation of the lift apparatus responsive to determining that the obstacle is within a threshold distance above the refuse vehicle (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120; Koga ¶ [0085]: the sensor(s) 1210 detect barrier 1330 and the controller initiates a control action when barrier 1330 enters safety zone 1320. In some embodiments, the control action includes generating an alert to the operator of the refuse vehicle 10 indicating the presence of obstacles 908 above the refuse vehicle 10. In some embodiments, the control action additionally and/or alternatively includes controlling an aspect of the refuse vehicle 10. For example, the control action may include limiting the movement of the refuse vehicle 10 so as to prevent it from coming into contact with barrier 1330).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to further include the distance sensors for detecting overhead obstacles to prevent a lifting operation of Koga with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to allow a refuse vehicle to avoid detected obstacles including power lines (Koga ¶ [0076]).
Regarding claim 17, the combination of Mahan, Williams, Takao, and Koga discloses further comprising:
a camera (Koga ¶ [0045]: Data captured by the sensor(s) 422 may include, for example, raw image data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.) that may be used to detect objects. For example, the sensor(s) 422 may include a camera and/or software component configured to determine a distance to obstacles identified in images from the camera) disposed on a top of the refuse vehicle, the camera configured to detect a relative distance of an obstacle that is overhead of the refuse vehicle (Koga ¶ [0072]: In some embodiments, the distance is calculated by the controller using data provided by the sensor(s) 1010 and machine learning techniques; Koga ¶ [0084]: scenario 1300 illustrates the refuse vehicle 10 underneath a barrier, shown as barrier 1330. Barrier 1330 may be a parking structure, overhang, bridge, bypass, or any other obstacle that may be above the refuse vehicle 10. In scenario 1300 the refuse vehicle 10 is traveling along direction 1340 towards and under barrier 1330. In some embodiments, barrier 1330 is located in a blind spot that is an area that cannot be seen by an operator of the refuse vehicle 10. In some embodiments, the sensor(s) 1210 are positioned on the top of the refuse vehicle 10. For example, the sensor(s) 1210 may be placed on top of the refuse vehicle 10 at the front and rear of the vehicle and detect obstacles);
wherein the processing circuitry is configured to prevent operation of the lift apparatus responsive to determining that the obstacle is within a threshold distance above the refuse vehicle (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120; Koga ¶ [0085]: the sensor(s) 1210 detect barrier 1330 and the controller initiates a control action when barrier 1330 enters safety zone 1320. In some embodiments, the control action includes generating an alert to the operator of the refuse vehicle 10 indicating the presence of obstacles 908 above the refuse vehicle 10. In some embodiments, the control action additionally and/or alternatively includes controlling an aspect of the refuse vehicle 10. For example, the control action may include limiting the movement of the refuse vehicle 10 so as to prevent it from coming into contact with barrier 1330).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to further include the camera for detecting overhead obstacles to prevent a lifting operation of Koga with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to allow a refuse vehicle to avoid detected obstacles including power lines (Koga ¶ [0076]).
Regarding claim 19, the combination of Mahan, Williams, Takao, and Koga discloses further comprising a distance sensor (Koga ¶ [0045]: Data captured by the sensor(s) 422 may include, for example, raw image data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.) that may be used to detect objects. For example, the sensor(s) 422 may include a camera and/or software component configured to determine a distance to obstacles identified in images from the camera) disposed on a lift arm of the lift apparatus (Koga: sensor 1110 in Fig. 11 and sensor 1410 in Fig. 14 positioned on the arm of the lift apparatus; Koga ¶ [0046]: The sensor(s) 422 may be disposed at any number of locations throughout and/or around the refuse vehicle 10 for capturing image and/or object data from any direction with respect to the refuse vehicle 10 … In some embodiments, one or more of sensor(s) 422 may be located on an attachment utilized by the refuse vehicle 10, such as container attachment 60 described above. It should be understood that sensor(s) may be positioned anywhere on the refuse vehicle 10), the distance sensor configured to detect a relative distance between an obstacle and the lift arm of the lift apparatus, wherein the processing circuitry is configured to limit further operation of the lift apparatus in response to detecting that the obstacle is within a threshold distance of the lift arm (Koga ¶ [0072]: the controller may not allow an operator of the refuse vehicle 10 to operate the side-lift assembly 1020 within a set distance of the barrier 1030. The distance may be based off of dimensions of the refuse vehicle 10 and/or the side-lift assembly 1020. In some embodiments, the distance may be a default minimum distance. In some embodiments, an operator sets the distance. In some embodiments, the distance is calculated by the controller using data provided by the sensor(s) 1010 and machine learning techniques).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to further include the distance sensor on a lifting arm for detecting obstacles to prevent a lifting operation of Koga with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to allow a refuse vehicle to avoid detected obstacles including power lines (Koga ¶ [0076]).
Claims 15 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2021/0292086 by Mahan et al. (herein after “Mahan”), in view of U.S. Patent Application Publication No. US 2020/0339347 by Williams et al. (herein after “Williams”), WO 2021/171974 by Takao (herein after “Takao”) and U.S. Patent Application Publication No. US 2021/0325529 by Koga et al. (herein after “Koga”), further in view of U.S. Patent Application Publication No. US 2009/0108840 by Givens (herein after “Givens”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 15, the combination of Mahan, Williams, Takao, and Koga discloses further comprising:
an electromagnetic radiation (“EMR”) detector (Koga ¶ [0045]: The sensor(s) 422 may include any type of device that is configured to capture data associated with the detection of objects such as refuse containers and/or pedestrians. The sensor(s) 422 includes any one and/or a combination of proximity sensors, infrared sensors, electromagnetic sensors, capacitive sensors, photoelectric sensors, inductive sensors, radar, ultrasonic sensors, Hall Effect sensors, fiber optic sensors, Doppler Effect sensors, magnetic sensors, laser sensors (e.g., LIDAR sensors), sonar, and/or the like)
wherein the processing circuitry (Koga: controller 500 in Fig. 5) is further configured to:
obtain feedback from the EMR detector (Koga ¶ [0070]: The sensor(s) 612 collect data that may indicate the presence of obstacles around the refuse vehicle 10 and send the data to the controller);
determine, based on the feedback, whether the power line is present overhead of the refuse vehicle within a threshold distance above the refuse vehicle (Koga ¶ [0074]: Scenario 1100 illustrates a refuse vehicle 10 underneath an obstacle shown as power lines 1120; Koga ¶ [0076]: the controller is configured to detect the power lines 1120 within the path of trajectory 1430. For example, the controller may detect power lines 1120 within the trajectory 1430 of refuse container 60 and front-lift assembly 40 of the refuse vehicle 10; power lines 1120 in Fig. 11); and
prevent operation of the lift apparatus responsive to determining that the power line is present within the threshold distance above the refuse vehicle (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120).
It is noted that the combination of Mahan, Williams, Takao, and Koga discloses electromagnetic sensors and overhead power line detection using sensors but does not explicitly disclose an electromagnetic radiation (“EMR”) detector configured to detect a presence of a power line overhead of the refuse vehicle.
However, Givens, in the same field of endeavor, teaches an electromagnetic radiation (“EMR”) detector configured to detect a presence of a power line overhead of the refuse vehicle (Givens ¶ [0023]: FIG. 3 is an illustrative diagram of one embodiment of a wireless sensor (300) configured to sense the electromagnetic signature of a power line (130, FIG. 1); Givens ¶ [0028]: According to one exemplary embodiment, the variation in the antenna geometries gives each sub sensor (comprised of an antenna/electronics pair) a varying sensitivity to an electromagnetic field. As the boom (130) approaches a power line, the sensor (300) passes into the electromagnetic field generated by the passage of current through the power line (150). According to the exemplary configuration, the first sub sensor (305, 330) is the most efficient at sensing the electromagnetic field and converting the electromagnetic field into energy. This energy powers the electronics segment (330) which transmits its wireless signal to the base station).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to further include the sensors for detecting overhead powerlines to prevent a lifting operation of Koga and the electromagnetic sensors of Givens with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to allow a refuse vehicle to avoid detected obstacles including power lines (Koga ¶ [0076]) and sense proximity of mobile equipment relative to power lines and to prevent contact by the equipment with the power line (Givens ¶ [0006]).
Regarding claim 18, the combination of Mahan, Williams, Takao, and Koga discloses further comprising an EMR detector (Koga ¶ [0045]: The sensor(s) 422 may include any type of device that is configured to capture data associated with the detection of objects such as refuse containers and/or pedestrians. The sensor(s) 422 includes any one and/or a combination of proximity sensors, infrared sensors, electromagnetic sensors, capacitive sensors, photoelectric sensors, inductive sensors, radar, ultrasonic sensors, Hall Effect sensors, fiber optic sensors, Doppler Effect sensors, magnetic sensors, laser sensors (e.g., LIDAR sensors), sonar, and/or the like) disposed on a lift arm of the lift apparatus (Koga: sensor 1110 in Fig. 11 and sensor 1410 in Fig. 14 positioned on the arm of the lift apparatus; Koga ¶ [0046]: The sensor(s) 422 may be disposed at any number of locations throughout and/or around the refuse vehicle 10 for capturing image and/or object data from any direction with respect to the refuse vehicle 10 … In some embodiments, one or more of sensor(s) 422 may be located on an attachment utilized by the refuse vehicle 10, such as container attachment 60 described above. It should be understood that sensor(s) may be positioned anywhere on the refuse vehicle 10), the (Kago ¶ [0075]: the user interface displays a distance between the refuse vehicle 10 and power lines 1120. The distance may be displayed numerically. In some embodiments, the user interface displays the distance graphically with a digital representation of the refuse vehicle 10 and power lines 1120), wherein the processing circuitry is configured to limit further operation of the lift apparatus in response to detecting that the power line is within a threshold distance of the lift arm (Koga ¶ [0076]: the controller initiates a control action in response to detecting an power lines 1120 within trajectory 1430 in order to avoid the detected obstacle. For example, the controller is configured to automatically stop the motion of front-lift assembly 40 to avoid power lines 1120).
It is noted that the combination of Mahan, Williams, Takao, and Koga discloses electromagnetic sensors and overhead power line detection using sensors but does not explicitly teach the EMR detector configured to detect a relative distance between a power line and the lift arm of the lift apparatus.
However, Givens, in the same field of endeavor, teaches the EMR detector configured to detect a relative distance between a power line and the lift arm of the lift apparatus (Givens ¶ [0023]: FIG. 3 is an illustrative diagram of one embodiment of a wireless sensor (300) configured to sense the electromagnetic signature of a power line (130, FIG. 1); Givens ¶ [0028]: According to one exemplary embodiment, the variation in the antenna geometries gives each sub sensor (comprised of an antenna/electronics pair) a varying sensitivity to an electromagnetic field. As the boom (130) approaches a power line, the sensor (300) passes into the electromagnetic field generated by the passage of current through the power line (150). According to the exemplary configuration, the first sub sensor (305, 330) is the most efficient at sensing the electromagnetic field and converting the electromagnetic field into energy. This energy powers the electronics segment (330) which transmits its wireless signal to the base station).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan modified by the detection of fork pockets of a refuse container and determining fork assembly movements for engaging the fork pockets of Williams, the detection of container orientation when determining a trajectory for engaging forks with pockets of a container of Takao, and the detection of overhead obstacles and determination of an autonomous path that moves away from the overhead obstacles of Koga to further include the sensors attached to a lift arm for detecting a distance to overhead powerlines to prevent a lifting operation of Koga and the electromagnetic sensors of Givens with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to allow a refuse vehicle to avoid detected obstacles including power lines (Koga ¶ [0076]) and sense proximity of mobile equipment relative to power lines and to prevent contact by the equipment with the power line (Givens ¶ [0006]).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2021/0292086 by Mahan et al. (herein after “Mahan”), in view of WO 2023/192599 by Ghike et al. (herein after “Ghike”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 20, Mahan discloses a method of controlling operation of a refuse vehicle (Mahan: refuse vehicle 10 in Fig. 1B), the method comprising:
obtaining sensor data of a site from a sensor of a (Mahan ¶ [0062]: At step 702 data is received from one or more image and/or object sensors (e.g., image/object sensors 430) disposed at various locations of a refuse vehicle. In some embodiments, data is received from at least a visible light camera and a LIDAR camera or sensor. Received data may include raw data from one or more cameras (e.g., visible light cameras) and/or data from one or more sensors (e.g., LIDAR, radar, etc.), as described above. In various embodiments, the data includes still images, video, or other data that can be used to detect an object or objects);
autonomously controlling a (Mahan ¶ [0077]: In autonomous and/or semi-autonomous operations, the refuse vehicle (e.g., refuse vehicle 10) and actuator assembly (e.g., actuator assembly 436) may be controlled or commanded (e.g., by control module 424) to automatically navigate to the refuse can. For example, the refuse vehicle may automatically move to the refuse can, and the actuator may automatically move to engage the refuse can, without operator input).
It is noted that Mahan fails to particularly disclose obtaining sensor data of a site from a sensor of a first refuse vehicle;
determining a profile of the site including an obstacle map using the sensor data; and
autonomously controlling a second refuse vehicle based on the obstacle map such that the second refuse vehicle avoids obstacles while transporting and operating a lift apparatus at the site.
However, Ghike, in the same field of endeavor, teaches obtaining sensor data of a site from a sensor of a first refuse vehicle (Ghike ¶ [0053]: the sensors 385 may include a map sensor that acquires data indicative of or, if virtual, determines map data (e.g., the map data 334). Accordingly, the sensors 385 may include a positioning sensor (e.g., a GPS sensor, a GNSS sensor, a RTK sensor, etc.), a computer vision sensor (e.g., a camera, a radar sensor, a LIDAR, sensor, etc.), and/or other suitable sensor for detecting the position of the vehicle 202 and/or a position of one or more objects proximate the vehicle 202, such as a shipping container, the machinery 190, etc);
determining a profile of the site including an obstacle map using the sensor data (Ghike ¶ [0026]: The map data 134 may also include the location of one or more components of the machinery 190, obstacles that may block a vehicle from moving along a road or path, and/or other information related to generating a map of the predetermined location. In some embodiments, the map data 134 may include sensor data detected by one or more sensors, such as the vehicle sensors 385 shown in FIG. 2, and/or other sensors associated with the predetermined location. The sensor data may include three-dimensional image data that depicts the location of the roads, paths, machinery components, obstacles, and/or other objects within the predetermined location; Ghike ¶ [0040]: Accordingly the map generation circuit 142 may use the previously generated maps to generate a new map. In some embodiments, the map generation circuit 142 may be structured to update a previously generated map with new sensor data received from one or more vehicles 202); and
autonomously controlling a second refuse vehicle based on the obstacle map such that the second refuse vehicle avoids obstacles while transporting and operating a lift apparatus at the site (Ghike ¶ [0015]: the systems, methods, and apparatuses described herein provide a technical solution to the technical problem of autonomous vehicle route planning by providing an improved, centralized maps to each of the vehicles in a fleet, in real-time or near real-time, such that each of the vehicles uses the most up-to-date map available for route planning to improve autonomous operation (e.g., avoid collisions with obstacles); Ghike ¶ [0026]: The map may be used to enable the vehicles 202 to autonomously navigate the predetermined area; Ghike ¶ [0039]: the map generation circuit 142 receives the map data 134, analyses the map data 134 and transforms the map data 134 into a useable map, such as a three-dimensional map, for enabling autonomous control of the vehicles 202).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the refuse vehicle and system for detecting refuse containers and determining trajectories for a refuse vehicle to approach and engage refuse containers of Mahan to include the centralized obstacle map for avoiding obstacles when determining trajectories for a fleet of vehicles of Ghike with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to improve autonomous vehicle operation and obstacle avoidance by providing the most up-to-date obstacle maps to a vehicle in a fleet (Ghike ¶ [0015]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to the applicant’s disclosure:
US 2021/0024068 discloses an autonomous waste collection truck that detects refuse bins while following a route that can be adjusted based on detected obstacles or refuse bins ([0027]-[0042]).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICHOLAS P LANGHORNE whose telephone number is (571)272-5670. The examiner can normally be reached M-F 8:30-5:30.
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/N.P.L./Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
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