2181results about "Position/course control in two dimensions" patented technology

In various examples, teleoperation architectures for safe control of machines are described. Systems and methods are disclosed that use an end-to-end safety architecture that covers both a vehicle or machine and a remote system providing a control center, where the vehicle or machine is at least partly or temporarily configured for control by the remote system. In some examples, the end-to-end architecture uses a layered safety policy monitoring system, where the remote system uses first policies to ensure that operator commands are viable and the vehicle uses second policies to ensure that the operator commands are safe to perform (e.g., will not cause collisions with other objects). Additionally, in some examples, the end-to-end architecture allows for the vehicle to perform minimum risk maneuvers, also referred to as “control fallbacks,” if problems were to occur.

A system includes a camera, a robot, and a management system. The camera is configured to capture one or more images of a material handling environment. The material handling environment normally includes one or more items. The robot is at least in part configured to move along a travel path relative to the items, and the robot is configured to pick the items. The management system is configured to monitor the material handling environment through the images from the camera. The management system is configured to determine dynamically multiple picking solutions for the items in real-time while the robot moves along the travel path.

The described aspects and implementations enable efficient and seamless tracking of objects in vehicle environments using different sensing modalities across a wide range of distances. A perception system of a vehicle deploys an object tracking pipeline with a plurality of models that include a camera model trained to perform, using camera images, object tracking at distances exceeding a lidar sensing range, a lidar model trained to perform, using lidar images, object tracking at distances within the lidar sensing range, and a camera-lidar model trained to transfer, using the camera images and the lidar images, object tracking from the camera model to the lidar model.

To provide a travel control system in which a travel position of a work vehicle easily becomes a proper position.SOLUTION: There is provided a travel control system for controlling travel of a work vehicle having a positioning unit 80. The positioning unit 80 comprises: a reference determination part which is configured to measure a position of the positioning unit 80, and determines a reference part ST out of the work vehicle; a position calculating part which calculates a position of the reference part ST on the basis of a measurement result by the positioning unit 80; a path generation part which generates a target path LI for travel of the work vehicle; and a travel control part which performs distance control for controlling travel of the work vehicle so that a distance between the reference part ST and the target path LI becomes a prescribed distance Y, where the reference determination part changes the reference part ST according to a work state of the work vehicle.SELECTED DRAWING: Figure 7

A forklift autonomous operation system is disclosed. The forklift autonomous operation system includes a forklift having a load handling system, the load handling system including a mast and a plurality of forks and a camera, coupled to the load handling system, for obtaining visual input data of an environment. Further, the system includes a plurality of sensors coupled to the forklift for obtaining sensor data and a control system configured to process the visual input data and the sensor data.

A robot in accordance with at least some embodiments of the present technology includes a neck region through which the robot is configured to transmit and receive light. The robot defines a robot height and includes a body, a head carried by the body, and a neck extending between the head and the body along the robot height. The robot further includes a structural neck frame at a periphery of the neck in a plane perpendicular to the robot height. The structural neck frame defines windows distributed around the periphery of the neck. The robot further includes a sensor disposed at least partially within the structural neck frame. The sensor includes a laser configured to transmit light via the windows and a detector configured to receive light via the windows. A field of view of the sensor extends at least 320 degrees around the neck.

A method includes registering a plurality of work vehicles with a work vehicle system, and selecting a particular work vehicle, from among the plurality of work vehicles which have been registered with the work vehicle system, to use as a route recording work vehicle to record a new route. The registering the plurality of work vehicles with the work vehicle system can include, for each of the plurality of work vehicles, receiving an identifier that corresponds to the respective work vehicle, and receiving a confirmation to register the respective work vehicle in the work vehicle system.

An automated storage and retrieval system includes an automated storage and retrieval grid and a delivery system. The automated storage and retrieval grid includes a container handling vehicle rail system and a delivery column. The container handling vehicle rail system is for guiding a plurality of container handling vehicles. The delivery column is adapted for transport of a storage container from a container handling vehicle to a delivery port situated at a lower end of the delivery column, and further adapted for transport of a storage container from the delivery port to the container handling vehicle. The storage container is configured to be stored in a stack of storage containers beneath the container handling vehicle rail system. The delivery system includes a remotely operated delivery vehicle, which includes a container carrier adapted to support the storage container. The delivery vehicle is further adapted to transport the storage container between a delivery port and a second location for handling of the storage container by at least one of a robotic operator and a human operator.

Apparatus, methods, and computer program products for platoon formation are provided. An example method may include identifying a set of non-malicious vehicles based on at least one of data associated with the set of non-malicious vehicles or communication from a second vehicle or a RSU. The example method may further include transmitting a request message to the set of non-malicious vehicles. The example method may further include receiving an acceptance message from at least one vehicle of the set of non-malicious vehicles. The example method may further include configuring a platoon with the at least one vehicle of the set of non-malicious vehicles.

A container accessing station which has been configured to offer multiple access points where access to each access point may be permitted through an upper working surface of the container accessing station to an underlying container that has been delivered to the access point. The working surface is provided by one or more working surface sections, each working surface section having a common attachment configuration to allow either an access panel or a blanking-off panel to be fitted as part of the container accessing station at any of the multiple access points.

The present invention relates to self-propelled airside dollies (100), and particularly but not exclusively to airside baggage dollies and airside cargo dollies, and autonomous airside dollies. The self-propelled airside dolly comprises a cargo portion (104) configured to hold baggage or cargo, a drive system (108) for driving the self-propelled airside dolly (100), a controller (114) configured to control the drive system (108) in response to control signals and a processor (116) configured to provide the control signals to the controller (114).

The disclosure relates to the system and methods for generating a guidance path for automated navigation of large agricultural equipment. Vehicle path data from leading vehicles can be recorded, stored or inputted into the system for generation of guidance paths offset from the swaths traversed by the leading vehicle. Combines, planters sprayers and other vehicles utilizing guidance system can be used to record leading vehicle data for use by the following vehicle in real time or in subsequent cycles. Enterprise systems can manage multiple grain carts and / or combines or other vehicles to maximize efficiency.

A sensor calibration system (5) for watercraft (1), comprising: a primary environment sensor (6. 7) configured to detect an external object including a region of the watercraft and a distance to the external object, and mounted to a part of the watercraft; and a processor (11) for processing an output of the environment sensor, wherein the processor is configured to identify a bow of the watercraft from the output of the primary environment sensor, and calibrate a position and an orientation of the primary environment sensor relative to the bow.

Systems and methods for swarm adaptation based on social value orientations are provided. In one embodiment, a method includes calculating social value orientations for a proximate vehicle of a plurality of proximate vehicles on a roadway with a plurality of swarm vehicles of a swarm. The method includes determining a total cost for the one or more proximate vehicles based on the social value orientations. The total cost for the proximate vehicle is based on an individual cost of the proximate vehicle and a joint cost of the proximate vehicle relative to the roadway vehicles. The method includes generating a global objective function based on a summation of the total cost of the plurality of proximate vehicles. The method includes determining a swarm action for a swarm vehicle by minimizing the total cost of the global objective function. The method includes causing the swarm vehicle to execute the swarm action.

Robotic systems and associated methods are described herein. The robotic system may collect measurements from various sensors corresponding to motion of the robotic system, the surrounding environment of the robotic system, or both. The robotic system may generate measurement data based on the collected measurements. Measurements from a particular sensor may be processed in conjunction with different sensors of the robotic system, which may facilitate more accurate or more useful measurement data. The systems and methods of the present disclosure enable the detection, labeling, and locating of features in real time or near real time using the robotic system with little or no reliance on human interaction to detect and map the features. The disclosure provides enhanced accuracy and efficiency as it enhances the functionality and reduces the reliance on human detection of features.

An air vehicle management system comprising a controller for an air vehicle. The controller is configured to determine a prediction of an acceleration using an air vehicle model system and backscatter data. The air vehicle model system is trained to predict the acceleration using the backscatter data and is generated using backscatter light detected from emitting a laser beam in an atmosphere in a direction ahead of the air vehicle. The controller is configured to determine an adjustment to a number of flight control settings for the air vehicle that reduces a stress on the air vehicle using the prediction of the acceleration. The controller is configured to adjust the number of flight control settings using the adjustment.

A method for controlling a vehicle platoon, performed by a computer device, includes: establishing a communication connection with a first vehicle, wherein the first vehicle is a free vehicle; obtaining vehicle status information of the first vehicle; obtaining at least one platoon status information of at least one vehicle platoon; matching a first target vehicle platoon of the at least one vehicle platoon with the first vehicle based on the vehicle status information and the at least one platoon status information; generating a first platoon control instruction based on: a first distance between the first vehicle and the first target vehicle platoon, the vehicle status information, and platoon status information of the first target vehicle platoon; and instructing the first vehicle to join the first target vehicle platoon based on transmitting the first platoon control instruction to at least one of the first target vehicle platoon or the first vehicle.

Systems and methods for autonomous vehicle path planning are described herein. An example vehicle includes an image sensor to obtain an image of a scene of an area surrounding the vehicle. The vehicle also includes navigation system circuitry to: analyze the image and generate a semantically segmented image that identifies one or more types of features in the image; project the semantically segmented image to a two-dimensional (2D) map projection; convert the 2D map projection into a cost map; and determine a path for the vehicle based on the cost map.

Exemplary embodiments of the present disclosure are directed towards an indoor and outdoor navigation system for autonomous mobile robots and the methods employed therein. The system comprises a mobile robot equipped with sensors, including IMU, encoders, GPS, and a 3D camera, all managed by a processing device. During indoor navigation, the device utilizes an extended Kalman filter for precise odometry estimation, adapting to outdoor mode with an additional clearance base. User-defined waypoints guide the robot, supported by safety lanes generated through a lane generation algorithm to prevent off-roading in mapless environments. Visual markers facilitate odometry correction for enhanced accuracy, while map-based navigation employs 2D LIDAR sensors for environment mapping. Safety is ensured through obstacle detection and ground removal algorithms, with alerts transmitted via IoT protocols upon detecting obstacles beyond designated safety lanes, thereby enhancing navigation reliability and safety.

A vehicle platoon intersection decision-making system includes multiple vehicles. When executing the intersection decision-making process, the captain vehicle determines whether the platoon can pass through the intersection at the current speed command; if yes, the captain vehicle directs each vehicle to maintain travelling at the current speed command to pass through the intersection; if not, the captain vehicle generates a first optimized speed control information through a first speed decision-making process, making the platoon decelerate before reaching the intersection and begin to accelerate at an acceleration critical time point such that the platoon passes through the intersection. When the platoon passes through the intersection at the current speed command, no energy for accelerating or decelerating is wasted. The platoon decelerates first and then begins to accelerate at the appropriate time through the intersection, avoiding or reducing the time spent waiting for traffic lights at the intersection.

A virtual assist apparatus assists moving a tractor loader relative to a target item for mutually engaging the loader with the target item. An image sensor device generates target image data representative of a target item image. Based on the target image data, tractor heading data representative of a tractor heading of the tractor, and target alignment guidance data representative of a target approach path providing access to a target attachment feature of the target item that is mutually engageable with a corresponding loader attachment feature of the loader are determined. A display unit displays viewable images of tractor heading and the target approach path for assisting the movement of the tractor to position the loader relative to the target item for mutually engaging the loader with the target item. The target item may be an implement couplable with a tool carrier or a load engagable with the implement.

An agricultural vehicle includes a steering system configured to operate to steer the agricultural vehicle to perform a turn. The agricultural vehicle includes processing circuitry. The processing circuitry is configured to obtain an input indicating a specific turn to be performed by the steering system. The processing circuitry is configured to control the steering system of the agricultural vehicle to implement the specific turn based on the input and a model of the steering system of the agricultural vehicle while accounting for a time delay of the steering system due to slop of the steering system.

An autonomous vehicle navigation system includes a controller configured or programmed to receive information of a work vehicle, receive data input from a user, and cause the work vehicle to traverse a first plot, exit the first plot; traverse a margin area located between the first plot and an adjacent area or a second plot, and perform a turning maneuver process before entering a second row in the first plot. When the work vehicle performs the turning maneuver, the controller allows at least a portion of the work vehicle to reverse into the adjacent area or a third row included in the second plot based on the controller judging whether or not at least one or more conditions is satisfied, the one or more conditions being based on data detected from at least one sensor and / or the input data from the user.

A method to determine if a traffic situation comprising a plurality of heavy-duty vehicles following a plurality of guided vehicle trajectories in a defined area will lead to a vehicle deadlock is described. For example, one method includes generating a traffic situation representation for the defined area comprising, for each of the plurality of vehicles, an initial vehicle trajectory segment location and a subsequent deadlock status, inputting the traffic situation representation to a traffic situation deadlock classifier which has been trained to output a traffic situation deadlock classification based on an input representation of a traffic situation in the defined area, and, based on the input traffic situation representation, generating a predicted deadlock classification of a subsequent traffic situation for that input traffic situation representation.

In some embodiments, provided is a robot for water tunnel inspection, comprising: (a) a shell, comprising an upper shell and a lower shell; wherein the upper shell and the lower shell are sized and shaped to match each other, together defining a closed cavity therewithin; (b) a camera system, configured to capture an image or video of a field of view of surrounding; (c) a lighting system, configured to provide illumination at least partially for the field of view; (d) a propulsion system, configured to provide propulsion force to the robot in water; and (e) a controlling system, configured to provide power and control operation of the robot, wherein the robot is configured to float on water and to have a center of gravity positioned lower than geometric center. Other example embodiments are described herein. In certain embodiments, the robots provide safe and efficient tunnel inspections without human operation.

An automated storage and retrieval system includes an automated storage and retrieval grid and a delivery system. The automated storage and retrieval grid includes a container handling vehicle rail system and a delivery column. The container handling vehicle rail system, which is for guiding a plurality of container handling vehicles, includes a first set of parallel rails arranged in a horizontal plane and extending in a first direction, and a second set of parallel rails arranged in the horizontal plane and extending in a second direction which is orthogonal to the first direction, which first and second sets of rails form a grid pattern in the horizontal plane including a plurality of adjacent container handling vehicle grid cells. Each container handling vehicle grid cell includes a container handling vehicle grid opening defined by a pair of neighboring rails of the first set of rails and a pair of neighboring rails of the second set of rails. The delivery column is adapted for transport of a storage container arranged in a stack of storage containers beneath the container handling vehicle rail system between a container handling vehicle and a delivery port situated at a lower end of the delivery column. The delivery system includes a remotely operated delivery vehicle. The remotely operated delivery vehicle includes a vehicle body, rolling devices connected to the vehicle body, rolling device motors for driving the rolling devices in a horizontal plane, and a power source connected to the rolling device motors. A container carrier is adapted to support the storage container. The delivery vehicle is further adapted to transport the storage container between a delivery port and a second location for handling of the storage container by at least one of a robotic operator and a human operator.

An example system include one or more memories and one or more processors coupled to the one or more memories. The one or more processors are configured to perform a first segmentation operation on a previous frame of image data to generate first segmentation data. The one or more processors are configured to perform a deformable convolution operation based on the first segmentation data to generate a deformable convolution output. The one or more processors are configured to perform a second segmentation operation on a current frame of image data to generate second segmentation data. The one or more processors are configured to combine the deformable convolution output with the second segmentation data to generate third segmentation data and control operation of a device based on the third segmentation data.

A magnetic charging station and method of use is disclosed herein. The magnetic charging station is adapted to receive a robot and connect to the robot to charge a power source on the robot. The magnetic charging station is designed to improve the consistency and safety of charging by offering multiple mechanism to ensure proper alignment of the charging contacts. Having a tread receptacle that begins wide and narrows towards the end makes it easy for a robot entering the station to reach the correct position, and magnets assist in aligning and holding the robot to a charging contact. The charging contact on the charging station may be biased with a spring, allowing the charging contact to smoothly connect to a charging point on the robot. A method of use is further disclosed to describe the process of monitoring battery levels, managing multiple charging station in a network, and issuing instructions to the components of the system using a cloud connect software system.

An autonomous vehicle navigation system includes a controller configured or programmed to receive environment or location information a work vehicle detected by a sensor, receive user input data, and cause the work vehicle to traverse and exit a first row in the first plot, traverse a margin area located between the first plot and an adjacent field, and perform a turning maneuver process before entering a second row in the first plot. The controller determines, before the work vehicle starts driving, whether or not to turn on a turning area wider function based on a first condition group being satisfied based on the user input data. During the turning maneuver process, the controller judges whether or not the work vehicle is allowed to enter a third row of the adjacent field based on a second condition group being satisfied based on the information detected by the sensor.