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 . Claims 1-20 as originally filed are pending and have been considered as follows.
Priority
1. Acknowledgement is made that the present application is a national phase conversion of PCT/IB2024/060904 filed on 11/05/2024, which claims priority to CN202323371848.9 filed on 12/11/2023.
Information Disclosure Statement
2. The information disclosure statements (IDS) filed on 01/06/2025 and 05/14/2025 are being considered by the examiner.
Claim Objections
3. Claims 14 and 19 are objected to because of the following informalities:
Claim 14 is a method claim and should be re-written in independent format with other limitations of claims 1. In addition, the phrase “A method for a forklift…” is incomplete. It is unclear if the applicant intended to state “A method for operating a forklift…” or similar language.
Claim 19 is a method claim and should be re-written in independent format with other limitations of claims 1. In addition, the phrase “A method for a forklift…” is incomplete. It is unclear if the applicant intended to state “A method for operating a forklift…” or similar language.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
4. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
5. Claims 7 and 10-11 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Specification is utilized for the description citations below.
Regarding claim 7, the phrase “the driver is configured to drive a power mechanism…” is unclear. It is unclear what constitute as a driver and the specification does not provide a definition for what “a driver” is. For examination purposes, examiner has interpreted “driver” as any actuator/motor/or mechanism to drive the forklift.
Regarding claim 10, the phrase “an included angle between the first 3D laser radar and a horizontal plane is formed…” is unclear. It is unclear how the relationship between the mounting surface of the first 3D laser radar and the horizontal plane is established and unclear from which direction the angle is formed between the first 3D laser radar and the horizontal plane.
Regarding claim 11, the phrase “an included angle between the second 3D laser radar and a vertical plane is formed …” is unclear. It is unclear how the relationship between the mounting surface of the second 3D laser radar and the vertical plane is established and unclear from which direction the angle is formed between the second 3D laser radar and the vertical plane.
Claim Rejections - 35 USC § 102
6. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
7. Claims 1-3, 5-7 and 10-20 is/are rejected under 35 U.S.C. 102(a)(2)/(a)(1) as being anticipated by Faconti et al. (US 20250059011, hereinafter Faconti).
Regarding claim 1, Faconti teaches a forklift (see at least Figs. 1A-1C and [0103]: “…robotic vehicle 100 in the form of an AMR forklift…”), comprising:
a forklift body (see at least Figs. 1A-1C and [0104]: “The robotic vehicle 100 can also include a main housing 115 within which various control elements and subsystems can be disposed, including those that enable the robotic vehicle to navigate from place to place.”); and
a first three-dimensional (3D) laser radar and a second 3D laser radar (see at least Figs. 1A-1C and [0109]: “In some embodiments, the sensors 150 can include one or more stereo cameras 152 and/or other volumetric sensors, sonar sensors, radars, and/or laser imaging, detection, and ranging (LiDAR) scanners or sensors 154, as examples. In the embodiment shown in FIG. 1, there are two LiDAR devices 154a, 154b positioned at the top left and right of the robotic vehicle 100. In the embodiment shown in FIG. 1, at least one of the LiDAR devices 154a,b can be a 2D or 3D LiDAR device. In alternative embodiments, a different number of 2D or 3D LiDAR device are positioned near the top of the robotic vehicle 100. Also, in this embodiment a LiDAR 157 is located at the top of the mast.”),
wherein the first 3D laser radar and the second 3D laser radar are respectively mounted on different mounting surfaces on a top of the forklift body, such that a scanning region of the first 3D laser radar is independent of or partially overlapped with a scanning region of the second 3D laser radar (see at least Figs. 1A-1C and [0109]: “In some embodiments, the sensors 150 can include one or more stereo cameras 152 and/or other volumetric sensors, sonar sensors, radars, and/or laser imaging, detection, and ranging (LiDAR) scanners or sensors 154, as examples. In the embodiment shown in FIG. 1, there are two LiDAR devices 154a, 154b positioned at the top left and right of the robotic vehicle 100. In the embodiment shown in FIG. 1, at least one of the LiDAR devices 154a,b can be a 2D or 3D LiDAR device. In alternative embodiments, a different number of 2D or 3D LiDAR device are positioned near the top of the robotic vehicle 100. Also, in this embodiment a LiDAR 157 is located at the top of the mast.”).
Regarding claim 2, Faconti teaches the limitations of claim 1. Faconti further teaches fork arms, wherein the fork arms are connected with the forklift body and at a first side of the forklift body (see at least Figs. 1B- 1C and [0104]: “In this embodiment, the robotic vehicle 100 includes a payload area 102 configured to transport a pallet 104 loaded with goods, which collectively form a palletized payload 106. To engage and carry the pallet 104, the robotic vehicle may include a pair of forks 110, including a first and second forks 110a, b.”);
the scanning region of the first 3D laser radar comprises a front obliquely-upper region of a second side of the forklift body, wherein the second side of the forklift body and the first side of the forklift body are opposite to each other (see at least Figs. 1B-1C and [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system. In some embodiments, one or more of the sensors 150 can be used to collect sensor data used to represent the environment and objects therein using point clouds to form a 3D evidence grid of the space, each point in the point cloud representing a probability of occupancy of a real-world object at that point in 3D space.”; [0110]: “In various embodiments, sensor data from one or more of the sensors 150, e.g., one or more stereo cameras 152 and/or LiDAR scanners 154, can be used to generate and/or update a 2-dimensional or 3-dimensional model or map of the environment, and sensor data from one or more of the sensors 150, e.g., sensors 152 and/or 157, can be used for the determining location of the robotic vehicle 100 within the environment relative to the electronic map of the environment.”); and
the scanning region of the second 3D laser radar comprises a front region of the second side of the forklift body (see at least Figs. 1A-1C and [0109]: “In some embodiments, the sensors 150 can include one or more stereo cameras 152 and/or other volumetric sensors, sonar sensors, radars, and/or laser imaging, detection, and ranging (LiDAR) scanners or sensors 154, as examples. In the embodiment shown in FIG. 1, there are two LiDAR devices 154a, 154b positioned at the top left and right of the robotic vehicle 100. In the embodiment shown in FIG. 1, at least one of the LiDAR devices 154a,b can be a 2D or 3D LiDAR device. In alternative embodiments, a different number of 2D or 3D LiDAR device are positioned near the top of the robotic vehicle 100. Also, in this embodiment a LiDAR 157 is located at the top of the mast.”).
Regarding claim 3, Faconti teaches the limitations of claim 1. Faconti further teaches a third 3D laser radar (see at least Figs. 1B-1C and [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system.”; [0121]: “In various embodiments, the robotic vehicle 100 can include a payload engagement module 185. The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100.”),
wherein the third 3D laser radar is mounted on a first side of the forklift body, a scanning region of the third 3D laser radar includes a front obliquely-lower region of the first side, and the first side is a side of the forklift body connected with the fork arms of the forklift (see at least Figs. 1B-1C and [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system.”; [0121]: “In various embodiments, the robotic vehicle 100 can include a payload engagement module 185. The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100.”).
Regarding claim 5, Faconti teaches the limitations of claim 1. Faconti further teaches a support assembly, wherein the support assembly is on the top of the forklift body (see at least Figs. 1A-1C and [0109]: 3D Lidar device 154a and 3D Lidar device 157 are mounted on a mast on the forklift body.); and
the first 3D laser radar and the second 3D laser radar are respectively mounted on different mounting surfaces of the support assembly (see at least Figs. 1A-1C and [0109]: 3D Lidar device 154a and 3D Lidar device 157 are mounted on different mounting surfaces on the mast).
Regarding claim 6, Faconti teaches the limitations of claim 1. Faconti further teaches wherein the top of the forklift body comprises a first mounting surface and a second mounting surface (see at least Figs. 1A-1C and [0109]: the mast (top of the forklift body) comprises a first mounting surface and second mounting surface);
a ball head of the first 3D laser radar is on the first mounting surface, and a central axis of the ball head of the first 3D laser radar is perpendicular to the first mounting surface (see at least Figs. 1A-1C and [0109]: a round head of 3D Lidar device 157 is mounted on the top surface (first mounting surface) and a central axis of the round head is perpendicular to the first top surface); and
a ball head of the second 3D laser radar is disposed on the second mounting surface, and a central axis of the ball head of the second 3D laser radar is perpendicular to the second mounting surface (see at least Figs. 1A-1C and [0109]: a round head of 3D Lidar device 154a is mounted on the side surface (second mounting surface) and a central axis of the round head of device 154a is perpendicular to the side surface).
Regarding claim 7, Faconti teaches the limitations of claim 1. Faconti further teaches a controller and a driver (see at least Fig. 2 and [0105]: “The forks 110 may be supported by one or more robotically controlled actuators 111 coupled to a mast 114 that enable the robotic vehicle 100 to raise and lower and extend and retract to pick up and drop off loads, e.g., palletized loads 106. In various embodiments, the robotic vehicle may be configured to robotically control the yaw, pitch, and/or roll of the forks 110 to pick a palletized load in view of the pose of the load and/or horizontal surface that supports the load.”; [0117]: “As is shown in FIG. 2, in example embodiments, the robotic vehicle 100 includes various functional elements, e.g., components and/or modules, which can be housed within the housing 115. Such functional elements can include at least one processor 10 coupled to at least one memory 12 to cooperatively operate the vehicle and execute its functions or tasks.”; [0119]: “The navigation module 170 can communicate instructions to a drive control subsystem 120 to cause the robotic vehicle 100 to navigate its path within the environment.”);
wherein the controller is used for movement control, task scheduling and travel path planning of the forklift (see at least Fig. 2 and [0117]: “As is shown in FIG. 2, in example embodiments, the robotic vehicle 100 includes various functional elements, e.g., components and/or modules, which can be housed within the housing 115. Such functional elements can include at least one processor 10 coupled to at least one memory 12 to cooperatively operate the vehicle and execute its functions or tasks. The memory 12 can include computer program instructions, e.g., in the form of a computer program product, executable by the processor 10. The memory 12 can also store various types of data and information. Such data and information can include route data, path data, path segment data, pick data, location data, environmental data, and/or sensor data, as examples, as well as an electronic map of the environment.”) and
the driver is configured to drive a power mechanism of the forklift to perform a corresponding operation (see at least [0105]: “The forks 110 may be supported by one or more robotically controlled actuators 111 coupled to a mast 114 that enable the robotic vehicle 100 to raise and lower and extend and retract to pick up and drop off loads, e.g., palletized loads 106. In various embodiments, the robotic vehicle may be configured to robotically control the yaw, pitch, and/or roll of the forks 110 to pick a palletized load in view of the pose of the load and/or horizontal surface that supports the load.”; [0119]: “The navigation module 170 can communicate instructions to a drive control subsystem 120 to cause the robotic vehicle 100 to navigate its path within the environment.”).
Regarding claim 10, Faconti teaches the limitations of claim 1. Faconti further teaches wherein an included angle between the first 3D laser radar and a horizontal plane is formed, and ranges from 0° to 25° (see at least Figs. 1B-1C and [0109]: 3D lidar 157 is mounted on the top surface of the mast which forms an angle of ranging from 0°-25° between the lidar and a horizontal plane).
Regarding claim 11, Faconti teaches the limitations of claim 1. Faconti further teaches wherein an included angle between the second 3D laser radar and a vertical plane is formed, and ranges from 0° to 15° (see at least Figs. 1B-1C and [0109]: 3D lidar 154a is mounted on the side surface of the mast which forms an angle ranging from 0°-15° between the lidar and a vertical plane).
Regarding claim 12, Faconti teaches the limitations of claim 1. Faconti further teaches at least one of: a manual control handle, a touch screen, a tricolor alarm light, an emergency stop button, a voice broadcaster, an automatic charge interface, a clearance lamp, a switching button, a manual charge interface, a bottom obstacle avoidance laser radar, an in-place switch, or a fork tip safety sensor (see at least Figs. 1A and [0119]: “As examples, the sensors 150 can be configured to collect sensor data related to objects, obstructions, equipment, goods to be picked, hazards, completion of a task, and/or presence of humans and/or other robotic vehicles. The robotic vehicle 100 may also include a human user interface configured to receive human operator inputs, e.g., a pick or drop complete input at a stop on the path. Other human inputs could also be accommodated, such as inputting map, path, and/or configuration information.”).
Regarding claim 13, Faconti teaches the limitations of claim 1. Faconti further teaches at least one of: a fork tip safety sensor on a picking end of a fork arm of the forklift, wherein the fork tip safety sensor is configured to monitor an environment ahead of the fork arm; an in-place switch at a bottom of a first side of the forklift body, wherein the in-place switch is configured to detect whether a pallet is in place when the fork arm picks up the pallet; and, a bottom obstacle avoidance laser radar at a bottom of the forklift body (see at least Fig 1A, [0106-0111], and [0119-0121]: 3D Lidar(s) 154 located at the bottom of the forklift body senses objects and avoid moving into the objects.).
Regarding claim 14, Faconti teaches the limitations of claim 1. Faconti further teaches a method for a forklift (see at least Figs. 4-8), applied to the forklift according to claim 1, and comprising: when the forklift implements a positioning function, the forklift at least uses point cloud data scanned by the first 3D laser radar as determination basis; and/or, when the forklift implements a stereoscopic protection function, the forklift at least uses point cloud data scanned by the second 3D laser radar as determination basis (see at least [0106]: “The robotic vehicle 100 may include a plurality of sensors 150 that provide various forms of sensor data that enable the robotic vehicle 100 to safely navigate throughout an environment, engage with objects to be transported, and avoid obstructions. In various embodiments, the sensor data from one or more of the sensors 150 can be used for path navigation and obstruction detection and avoidance, including avoidance of detected objects, hazards, humans, other robotic vehicles, and/or congestion during navigation.”; [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system. In some embodiments, one or more of the sensors 150 can be used to collect sensor data used to represent the environment and objects therein using point clouds to form a 3D evidence grid of the space, each point in the point cloud representing a probability of occupancy of a real-world object at that point in 3D space.”).
Regarding claim 15, Faconti teaches the limitations of claim 14. Faconti further teaches when the forklift implements the positioning function, the forklift uses the point cloud data scanned by the first 3D laser radar and the second 3D laser radar as determination basis (see at least [0106]: “The robotic vehicle 100 may include a plurality of sensors 150 that provide various forms of sensor data that enable the robotic vehicle 100 to safely navigate throughout an environment, engage with objects to be transported, and avoid obstructions. In various embodiments, the sensor data from one or more of the sensors 150 can be used for path navigation and obstruction detection and avoidance, including avoidance of detected objects, hazards, humans, other robotic vehicles, and/or congestion during navigation.”; [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system. In some embodiments, one or more of the sensors 150 can be used to collect sensor data used to represent the environment and objects therein using point clouds to form a 3D evidence grid of the space, each point in the point cloud representing a probability of occupancy of a real-world object at that point in 3D space.”).
Regarding claim 16, Faconti teaches the limitations of claim 15. Faconti further teaches wherein the forklift further comprises a third 3D laser radar mounted at a first side of the forklift body (see at least Figs. 1B-1C and [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system.”; [0121]: “In various embodiments, the robotic vehicle 100 can include a payload engagement module 185. The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100.”), and the method comprises:
when the forklift implements the positioning function, the forklift uses the point cloud data scanned by the first 3D laser radar, the second 3D laser radar and the third 3D laser radar as determination basis (see at least [0106]: “The robotic vehicle 100 may include a plurality of sensors 150 that provide various forms of sensor data that enable the robotic vehicle 100 to safely navigate throughout an environment, engage with objects to be transported, and avoid obstructions. In various embodiments, the sensor data from one or more of the sensors 150 can be used for path navigation and obstruction detection and avoidance, including avoidance of detected objects, hazards, humans, other robotic vehicles, and/or congestion during navigation.”; [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system. In some embodiments, one or more of the sensors 150 can be used to collect sensor data used to represent the environment and objects therein using point clouds to form a 3D evidence grid of the space, each point in the point cloud representing a probability of occupancy of a real-world object at that point in 3D space.”).
Regarding claim 17, Faconti teaches the limitations of claim 14. Faconti further teaches when the forklift implements the stereoscopic protection function, the forklift at least uses the point cloud data scanned by the first 3D laser radar and the second 3D laser radar as determination basis (see at least [0106]: “The robotic vehicle 100 may include a plurality of sensors 150 that provide various forms of sensor data that enable the robotic vehicle 100 to safely navigate throughout an environment, engage with objects to be transported, and avoid obstructions. In various embodiments, the sensor data from one or more of the sensors 150 can be used for path navigation and obstruction detection and avoidance, including avoidance of detected objects, hazards, humans, other robotic vehicles, and/or congestion during navigation.”; [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system. In some embodiments, one or more of the sensors 150 can be used to collect sensor data used to represent the environment and objects therein using point clouds to form a 3D evidence grid of the space, each point in the point cloud representing a probability of occupancy of a real-world object at that point in 3D space.”).
Regarding claim 18, Faconti teaches the limitations of claim 17. Faconti further teaches wherein the forklift further comprises a third 3D laser radar mounted at a first side of the forklift body (see at least Figs. 1B-1C and [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system.”; [0121]: “In various embodiments, the robotic vehicle 100 can include a payload engagement module 185. The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100.”), and the method comprises:
when the forklift implements the stereoscopic protection function, the forklift uses the point cloud data scanned by the first 3D laser radar, the second 3D laser radar and the third 3D laser radar as determination basis (see at least [0106]: “The robotic vehicle 100 may include a plurality of sensors 150 that provide various forms of sensor data that enable the robotic vehicle 100 to safely navigate throughout an environment, engage with objects to be transported, and avoid obstructions. In various embodiments, the sensor data from one or more of the sensors 150 can be used for path navigation and obstruction detection and avoidance, including avoidance of detected objects, hazards, humans, other robotic vehicles, and/or congestion during navigation.”; [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system. In some embodiments, one or more of the sensors 150 can be used to collect sensor data used to represent the environment and objects therein using point clouds to form a 3D evidence grid of the space, each point in the point cloud representing a probability of occupancy of a real-world object at that point in 3D space.”).
Regarding claim 19, Faconti teaches the limitations of claim 1. Faconti further teaches method for a forklift (see at least Figs. 4-8), applied to the forklift according to claim 1 and comprising: the forklift travels along a direction ahead of a first side of the forklift for picking up goods, such that a fork arm at the first side of the forklift picks up a pallet (see at least [0104]: “In this embodiment, the robotic vehicle 100 includes a payload area 102 configured to transport a pallet 104 loaded with goods, which collectively form a palletized payload 106. To engage and carry the pallet 104, the robotic vehicle may include a pair of forks 110, including a first and second forks 110a, b…The robotic vehicle 100 can also include a main housing 115 within which various control elements and subsystems can be disposed, including those that enable the robotic vehicle to navigate from place to place.”);
the forklift obtains point cloud data by using a third 3D laser radar at the first side of the forklift body to determine a state of the fork arm, a state of the pallet and a state of goods on the pallet, and to provide feedback to adjust the forklift (see at least Figs. 1A-1C and [0121]: “In various embodiments, the robotic vehicle 100 can include a payload engagement module 185. The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100. For example, the payload engagement module 185 can be configured to robotically control the actuators 111 and mast 114 to pick and drop payloads. In some embodiments, the payload engagement module 185 can be configured to control and/or adjust the pitch, yaw, and roll of the load engagement portion of the robotic vehicle 100, e.g., forks 110.”); and
the forklift runs away along a direction ahead of a second side of the forklift to, based on the point cloud data scanned by the first 3D laser radar, the second 3D laser radar and the third 3D laser radar, adjust a travel path of the forklift, wherein the first side is opposite to the second side (see at least [0104]: “In this embodiment, the robotic vehicle 100 includes a payload area 102 configured to transport a pallet 104 loaded with goods, which collectively form a palletized payload 106. To engage and carry the pallet 104, the robotic vehicle may include a pair of forks 110, including a first and second forks 110a, b…The robotic vehicle 100 can also include a main housing 115 within which various control elements and subsystems can be disposed, including those that enable the robotic vehicle to navigate from place to place.”).
Regarding claim 20, Faconti teaches the limitations of claim 19. Faconti further teaches wherein the forklift obtains the point cloud data by using the third 3D laser radar at the first side of the forklift body to determine the state of the fork arm, the state of the pallet and the state of the goods on the pallet, and to provide feedback to adjust the forklift (see at least [0121]: “In various embodiments, the robotic vehicle 100 can include a payload engagement module 185. The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100. For example, the payload engagement module 185 can be configured to robotically control the actuators 111 and mast 114 to pick and drop payloads. In some embodiments, the payload engagement module 185 can be configured to control and/or adjust the pitch, yaw, and roll of the load engagement portion of the robotic vehicle 100, e.g., forks 110.”), comprises:
determining, based on the point cloud data obtained by the third 3D laser radar, whether the fork arm is in place for the pallet (see at least [0107]: “One or more of the sensors 150 can form part of a two-dimensional (2D) or three-dimensional (3D) high-resolution imaging system. In some embodiments, one or more of the sensors 150 can be used to collect sensor data used to represent the environment and objects therein using point clouds to form a 3D evidence grid of the space, each point in the point cloud representing a probability of occupancy of a real-world object at that point in 3D space.”; [0121]: “The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100. For example, the payload engagement module 185 can be configured to robotically control the actuators 111 and mast 114 to pick and drop payloads. In some embodiments, the payload engagement module 185 can be configured to control and/or adjust the pitch, yaw, and roll of the load engagement portion of the robotic vehicle 100, e.g., forks 110.”);
when determining that an anomaly occurs to the pallet or the goods based on the point cloud data obtained by the third 3D laser radar, providing feedback and stopping the travel of the forklift, and adjusting a pose of the fork arm (see at least [0120]: “A safety module 130 can also make use of sensor data from one or more of the sensors 150, including LiDAR scanners 154, to interrupt and/or take over control of the drive control subsystem 120 in accordance with applicable safety standard and practices, such as those recommended or dictated by the United States Occupational Safety and Health Administration (OSHA) for certain safety ratings. For example, if safety sensors, e.g., sensors 154, detect objects in the path as a safety hazard, such sensor data can be used to cause the drive control subsystem 120 to stop the vehicle to avoid the hazard.”; [0121]: “In various embodiments, the robotic vehicle 100 can include a payload engagement module 185. The payload engagement module 185 can process sensor data from one or more of the sensors 150, such as payload area sensors 156, and generate signals to control one or more actuators 111 that control the engagement portion of the robotic vehicle 100. For example, the payload engagement module 185 can be configured to robotically control the actuators 111 and mast 114 to pick and drop payloads. In some embodiments, the payload engagement module 185 can be configured to control and/or adjust the pitch, yaw, and roll of the load engagement portion of the robotic vehicle 100, e.g., forks 110.”).
Claim Rejections - 35 USC § 103
8. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
9. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Faconti et al. (US 20250059011, hereinafter Faconti) in view of Yeo et al. (US 20210316975, hereinafter Yeo).
Regarding claim 4, Faconti teaches the limitations of claim 1. Faconti further teaches wherein the first 3D laser radar and the second 3D laser radar are aligned in a width direction of the forklift body (see at least Figs. 1B-1C and [0109]: “In the embodiment shown in FIG. 1, there are two LiDAR devices 154a, 154b positioned at the top left and right of the robotic vehicle 100. In the embodiment shown in FIG. 1, at least one of the LiDAR devices 154a,b can be a 2D or 3D LiDAR device. In alternative embodiments, a different number of 2D or 3D LiDAR device are positioned near the top of the robotic vehicle 100. Also, in this embodiment a LiDAR 157 is located at the top of the mast. Some embodiments LiDAR 157 is a 2D LiDAR used for localization.”).
Faconti fails to explicitly teach that the two sensors are aligned with each other in a width direction of the forklift body.
However, Yeo teaches an apparatus and system for an autonomous forklift truck that comprises a plurality of sensors that are aligned with each other in a width direction of the forklift body (see at least Fig. 1 and [0032]: “To begin with, the sensors mounted in the front part of the autonomous forklift truck is described as follows. A location recognition sensor 1 is equipped on top of the front part of the autonomous forklift truck. The location recognition sensor 1 is used to detect the location of the autonomous forklift truck in the work area, and may be LiDAR. In detail, the LiDAR may include a laser transmitter, a receiver and an operation and data processing module.”; [0034]: “Subsequently, a first sensor 2 and a second sensor 9 are equipped on the bottom and top in the front part of the autonomous forklift truck, respectively. The first sensor 2 equipped on the bottom in the front part of the autonomous forklift truck is equipped on one side of a front shock bumper of the autonomous forklift truck, and plays a role in detecting an obstacle near the work area floor.”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Faconti to incorporate the teachings of Yeo and provide a plurality of sensors that are aligned with each other in a width direction of the forklift body, with a reasonable expectation of success, in order to provide an alternative layout for the different sensors to capture data in the environment.
10. Claims 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Faconti et al. (US 20250059011, hereinafter Faconti) in view of Cavender-Bares (US 20170123424, hereinafter Cavender-Bares).
Regarding claim 8, Faconti teaches the limitations of claim 1. Faconti further teaches an upright column and a mounting platform, wherein the upright column is on the top of the forklift body, the mounting platform is connected with a top end of the upright column (see at least Figs. 1A-1C and [0109]: the mast comprises an upright portion and a mounting platform at the top of the upright portion to receive 3D Lidar 154a and 3D Lidar 157 located on the top of the forklift body), and the mounting platform is relative to the upright column; and
wherein the first 3D laser radar and the second 3D laser radar are respectively mounted on different mounting surfaces of the mounting platform (see at least Figs. 1A-1C and [0109]: 3D Lidar device 154a and 3D Lidar device 157 are mounted on different mounting surfaces on the mast).
Faconti fails to explicitly teach that the platform is vertically movable relative to the upright column.
However, Cavender-Bares teaches an apparatus and method for an autonomous vehicle platform that comprises a platform that is vertically movable relative to an upright column (see at least Fig. 15 and [0072]: “Referring to FIG. 15, in one embodiment, the onboard capabilities to detect, avoid, navigate around, or as appropriate navigate over a range of obstacles can include a sensor 175, such as one or more cameras, infrared sensors, ultrasonic sensors, or a combination thereof In one embodiment, sensor 175 is mounted to the top of a telescoping tower or mast 127. Telescoping tower or mast 127 can be deployed periodically, or only as needed. In another embodiment, mast 127 can be deployed in a partially or fully extended state during longer periods of operation.”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Faconti to incorporate the teachings of Cavender-Bares and provide a platform that is vertically movable relative to an upright column, with a reasonable expectation of success, in order to adjust the height of the sensors to provide additional detection coverage.
Regarding claim 9, Faconti teaches the limitations of claim 1. Faconti further teaches wherein the first 3D laser radar and the second 3D laser radar are both mounted on the top of the forklift body (see at least Figs. 1A-1C and [0109]: 3D Lidar device 154a and 3D Lidar device 157 are mounted on the top of the forklift body).
Faconti fails to explicitly teach that sensors are movably mounted on the top of the body.
However, Cavender-Bares teaches an apparatus and method for an autonomous vehicle platform that comprises sensors that are movably mounted on a top of a body (see at least Fig. 15 and [0072]: “Referring to FIG. 15, in one embodiment, the onboard capabilities to detect, avoid, navigate around, or as appropriate navigate over a range of obstacles can include a sensor 175, such as one or more cameras, infrared sensors, ultrasonic sensors, or a combination thereof In one embodiment, sensor 175 is mounted to the top of a telescoping tower or mast 127. Telescoping tower or mast 127 can be deployed periodically, or only as needed. In another embodiment, mast 127 can be deployed in a partially or fully extended state during longer periods of operation.”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Faconti to incorporate the teachings of Cavender-Bares and provide sensors that are movably mounted on a top of a body, with a reasonable expectation of success, in order to adjust the height of the sensors to provide additional detection coverage.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Fischer et al. (US 20180081369) teaches a method and apparatus for a mobile robot that comprises a plurality of sensors mounted on a robotic arm that sense information about the environment as the robotic arm moves.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIEN MINH LE whose telephone number is (571)272-3903. The examiner can normally be reached Monday to Friday (8:30am-5:30pm eastern time).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Khoi Tran can be reached on (571)272-6919. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/T.M.L./Examiner, Art Unit 3656
/KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656
