Abstract: A truck is provided that includes a bed section located rear of a cab section. The bed section is bounded on each side by opposing first and second upward-extending sidewalls, respectively. The truck also includes a truck bed cover that sits over the bed section on at least the first and second upward-extending sidewalls, and includes a door portion to create selective accessibility to the bed section of the pickup truck. The door portion is movable with respect to the first and second upward-extending sidewalls between open and closed positons via an automatic bed cover drive assembly that moves the door portion between open and closed positons according to a plurality of velocities within a predetermined variance.

Abstract: An autonomous driving device 100 is configured to set a target route to merge into a first main line L11 from a branch line L20 based on waypoints P set in a lane. If it is determined by the merge determination unit 14 that the merge is not easy, the target route setting unit 15 is configured to select the waypoint P on the branch line L20 set at the position on an end edge E side of the branch line L20 as the end edge waypoint Pa closest to the end edge E side on the branch line L20 to be selected for setting the target route, compared to a case where it is determined that the merge is easy.

Abstract: Systems and methods for detecting objects and predicting their motion are provided. In particular, a computing system can obtain a plurality of sensor sweeps. The computing system can determine movement data associated with movement of the autonomous vehicle. For each sensor sweep, the computing system can generate an image associated with the sensor sweep. The computing system can extract, using the respective image as input to one or more machine-learned models, feature data from the respective image. The computing system can transform the feature data into a coordinate frame associated with a next time step. The computing system can generate a fused image. The computing system can generate a final fused image. The computing system can predict, based, at least in part, on the final fused representation of the plurality of sensors sweeps from the plurality of sensor sweeps, movement associated with the feature data at one or more time steps in the future.

Abstract: A system and method for safely terminating navigation of an unmanned aerial vehicle (UAV). A method includes generating a navigation plan for the UAV, the UAV including a propulsion system, wherein the navigation plan includes at least a start point, an end point, and a virtual three-dimensional (3D) tunnel connecting the start and end points; and configuring the UAV to execute the navigation plan by navigating from the start point to the end point, wherein the UAV is configured such that the UAV executes the navigation plan by navigating from the start point to the end point, wherein the UAV is further configured such that the UAV terminates navigation by terminating power to the propulsion system of the UAV and deploying a failsafe, wherein the UAV is configured to terminate navigation when the UAV is outside of the 3D tunnel.

Abstract: An autonomous robot system to enable flexible, safe, efficient, and automated movement of goods and materials in a dynamic environment including one or more dynamic objects (e.g., humans). The autonomous robot system includes a modular autonomous ground vehicle (AGV) including a vehicle management system having a safety management system. The safety management system includes one or more safety management controllers to perform safety functions to enable the modular AGV to operate safely and efficiently alongside humans in a dynamic environment (e.g., a warehouse or fulfillment facility).

Abstract: This on-vehicle data management device includes: a data collection section configured to collect data that is obtained by a first apparatus of a vehicle and that is recorded in a record region provided in the first apparatus; an information obtaining section configured to obtain information related to travel of the vehicle from a second apparatus of the vehicle, the second apparatus being different from the first apparatus; and a storage processing section configured to store target data collected by the data collection section in association with the information related to travel of the vehicle obtained by the information obtaining section.

Abstract: Systems and methods for aerial unmanned vehicle (for example, drone) early warning privacy breach detection, interception, and defense are disclosed. The system detects drones within a threshold distance of an individual or configurable location, notifies the individual of the drones' existence, tracks the drones, and executes countermeasures. The system can communicate with telecommunication networks or other sources (for example, FAA) to identify and filter out drones that are authorized to be in the airspace around the individual.

Abstract: Various systems may benefit from appropriate thermal protection. For example, various flight recorder systems may benefit from thermal isolation of a flight recorder memory core. A system can include a memory core of a flight recorder. The system can also include an inner chamber housing the memory core. The system can further include an outer chamber housing the inner chamber with a vacuum between the inner chamber and the outer chamber. The system can additionally include a signal path from avionics equipment to the memory core through the outer chamber and the inner chamber. The system can also include a power path for the memory core through the outer chamber and the inner chamber.

Abstract: A technique for user interaction with an autonomous unmanned aerial vehicle (UAV) is described. In an example embodiment, perception inputs from one or more sensor devices are processed to build a shared virtual environment that is representative of a physical environment. The sensor devices used to generate perception inputs can include image capture devices onboard an autonomous aerial vehicle that is in flight through the physical environment. The shared virtual environment can provide a continually updated representation of the physical environment which is accessible to multiple network-connected devices, including multiple UAVs and multiple mobile computing devices. The shared virtual environment can be used, for example, to display visual augmentations at network-connected user devices and guide autonomous navigation by the UAV.

Abstract: The invention provides systems and methods for an autonomous vehicle (AV) and cloud control system, which comprises an AV control system comprising an onboard unit (OBU), a roadside unit (RSU) network, and a cloud-based platform. This integrated vehicle-road-cloud system provides traffic state estimation, prediction, computing, and control instructions for specific vehicles by the cloud-based platform. The cloud-based platform also provides safety and efficiency measures for vehicle operations and control under adverse weather conditions, and provides security, redundancy, and resiliency measures to improve system reliability. In addition, the RSU network provides high-resolution maps for specific vehicles.

Abstract: A computing system that analyzes the network effects of avoidance areas on autonomous vehicle routing is described herein. The computing system includes a data store that comprises a set of avoidance areas through which the autonomous vehicle is prohibited from being routed. A routing system generates an initial route from a source location to a target location irrespective of avoidance areas included on the initial route. When a number of avoidance areas on the initial route exceed a predetermined threshold, one or more alternative routes are generated from the source location to the target location that respectively circumvent a corresponding identified avoidance area on the initial route. Metrics are evaluated for the one or more alternative routes and a subset of avoidance areas are outputted to desirably be removed from the set of avoidance areas.

Abstract: A sensor is disclosed. The sensor may comprise: a housing, comprising a transmitting coil; and an optic assembly, comprising a body supporting at least one receiving coil and a conductive film that is in electrical contact with the at least one receiving coil, wherein, when the transmitting coil is energized, the at least one receiving coil is wirelessly energized causing a temperature of the film to increase.

Abstract: An electric vehicle includes first and second traveling motors, first and second rotational position sensors, and a measurement controller. The first rotational position sensor detects a rotation angle of the first traveling motor and has a first wheel-speed range in which a deviation of an original position of the first rotational position sensor is measurable. The second rotational position sensor detects a rotation angle of the second traveling motor and has a second wheel-speed range in which a deviation of an original position of the second rotational position sensor is measurable. The second wheel-speed range differs from the first wheel-speed range. The measurement controller executes, in an execution order, measurements of the deviations of the original positions of the first and second rotational position sensors while the electric vehicle is traveling, and switch the execution order on the basis of acceleration or deceleration data of the electric vehicle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting occupancies of agents. One of the methods includes obtaining scene data characterizing a current scene in an environment; and processing a neural network input comprising the scene data using a neural network to generate a neural network output, wherein: the neural network output comprises respective occupancy outputs corresponding to a plurality of agent types at one or more future time points; the occupancy output for each agent type at a first future time point comprises respective occupancy probabilities for a plurality of locations in the environment; and in the occupancy output for each agent type at the first future time point, the respective occupancy probability for each location characterizes a likelihood that an agent of the agent type will occupy the location at the first future time point.

Abstract: A method and system for estimating surface roughness of a ground for an off-road vehicle to control an implement comprises detecting motion data of an off-road vehicle traversing a field or work site during a sampling interval. A first sensor is adapted to detect pitch data of the off-road vehicle for the sampling interval to obtain a pitch acceleration. A second sensor is adapted to detect roll data of the off-road vehicle for the sampling interval to obtain a roll acceleration. An electronic data processor or surface roughness index module determines or estimates a surface roughness index based on the detected motion data, pitch data and roll data for the sampling interval. The surface roughness index can be displayed on the graphical display to a user or operator of the vehicle.

Abstract: A system and method for safely terminating navigation of an unmanned aerial vehicle (UAV). A method includes generating a navigation plan for the UAV, the UAV including a propulsion system, wherein the navigation plan includes at least a start point, an end point, and a virtual three-dimensional (3D) tunnel connecting the start and end points; and configuring the UAV to execute the navigation plan by navigating from the start point to the end point, wherein the UAV is configured such that the UAV executes the navigation plan by navigating from the start point to the end point, wherein the UAV is further configured such that the UAV terminates navigation by terminating power to the propulsion system of the UAV and deploying a failsafe, wherein the UAV is configured to terminate navigation when the UAV is outside of the 3D tunnel.

Abstract: A vehicle driving system that controls switching between automatic driving by a vehicle and manual driving by a driver of the vehicle includes a temperature sensor configured to monitor a temperature of an automatic driving ECU which controls the automatic driving; and a microcontroller configured to: (i) set a threshold temperature based on an estimated gradient of increase in the temperature of the automatic driving ECU, the estimated gradient of increase being estimated based on a drive state of an equipment installed on the vehicle, and (ii) in a case where the temperature of the automatic driving ECU that is sensed by the temperature sensor becomes equal to or greater than the threshold temperature, perform an operation for prompting the driver to switch to the manual driving during the automatic driving.

Abstract: Navigation devices and methods of operation are provided. The navigation device includes a communication unit; a display; an input unit for receiving an input of data; a communication unit; and a controller for controlling operation of the display and the input unit. The controller connects to a data server through the communication unit, requests path setting information to the data server, receives the path setting information from the data server, acquires present position information of the navigation device, acquires a user moving path by reflecting the acquired position information and the received path setting information, and sets the user moving path as a guidance path. In this case, the path setting information is generated in another electronic device or the data server based on user input information input from the another electronic device.

Abstract: Apparatuses and methods for predicting a crash using estimated vehicle speed. A set of sensor measurements are received from a mobile device disposed within a vehicle. A set of contiguous windows based on the sensor measurements may be defined. Each contiguous window represents a contiguous portion of the sensor measurements. A set of sensor measurements may be defined for each contiguous window. A trained neural network may execute, using the set of features, to generate one or more speed predictions. A vehicle crash prediction may be generated using the speed prediction. The vehicle crash prediction may then be transmitted to a remote device.

Abstract: A system and method for implementing reward based strategies for promoting exploration that include receiving data associated with an agent environment of an ego agent and a target agent and receiving data associated with a dynamic operation of the ego agent and the target agent within the agent environment. The system and method also include implementing a reward function that is associated with exploration of at least one agent state within the agent environment. The system and method further include training a neural network with a novel unexplored agent state.