Abstract: A system and method are provided for controlling movement of an implement for a self-propelled work vehicle, said implement comprising one or more components coupled to a main frame of the work vehicle. A linkage joint in defined in association with at least one implement component, wherein sensors are respectively associated with opposing sides of the linkage joint. Output signals from each sensor comprise sense elements which are fused in an independent coordinate frame associated at least in part with the respective linkage joint, wherein the independent coordinate frame is independent of a global navigation frame for the work vehicle. At least one joint characteristic (e.g., joint angle) is tracked based on at least a portion of the sense elements from the received output signals for each of the opposing sides of the respective linkage joint. Movement of implement components may optionally be controlled in view of the tracked joint characteristics.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating candidate future trajectories for agents. One of the methods includes obtaining scene data characterizing a scene in an environment at a current time point; for each of a plurality of lane segments, processing a model input comprising (i) features of the lane segment and (ii) features of the target agent using a machine learning model that is configured to process the model input to generate a respective score for the lane segment that represents a likelihood that the lane segment will be a first lane segment traversed by the target agent after the current time point; selecting, as a set of seed lane segments, a proper subset of the plurality of lane segments based on the respective scores; and generating a plurality of candidate future trajectories for the target agent.

Abstract: A ship body control device is provided, which includes a sensor, a propelling force controller, and an autopilot controller. The sensor measures a speed of a ship. The propelling force controller controls a propelling force of the ship. The autopilot controller outputs an instruction to reduce the propelling force to the propelling force controller, when a condition of canceling an automatic cruise in which the speed of the ship matches with an automatic ship speed setting is satisfied.

Abstract: Systems and methods for path planning with latent state inference and spatial-temporal relationships are provided. In one embodiment, a system includes an inference module, a policy module, a graphical representation module, and a planning module. The inference module receives sensor data associated with a plurality of agents. The inference module maps the sensor data to a latent state distribution to identify latent states of the plurality of agents. The latent states identify agents as cooperative or aggressive. The policy module predicts future trajectories of the plurality of agents at a given time based on sensor data and the latent states of the plurality of agents. The graphical representation module generates a graphical representation based on the sensor data and a graphical representation neural network. The planning module generates a motion plan for the ego agent based on the predicted future trajectories and the graphical representation.

Abstract: A distributed computing system for determining road surface traction capacity for roadways located in a common spatio-temporal zone includes a plurality of vehicles that each include a plurality of sensors and systems that collect and analyze a plurality of parameters related to road surface conditions in the common spatio-temporal zone. The distributed computing system also includes one or more central computers in wireless communication with each of the plurality of vehicles. The one or more central computers execute instructions to determine a road surface traction capacity value for the common spatio-temporal zone.

Abstract: In an unmanned aerial vehicle system S, a target position Pt to which UAV 1a is headed among a plurality of UAVs 1 is determined on the basis of a position of each of a plurality of ports 2, and the UAV 1a is controlled to fly toward the target position Pt. And then, a port 2x to be used for landing of the UAV 1a is determined on the basis of a reservation status of each of the plurality of ports 2 by the other UAV 1 different from the UAV 1a among the plurality of the UAVs 1 while the UAV 1a is flying toward the target position Pt, and the UAV 1a is controlled to fly toward the determined port 2x.

Abstract: A system includes a primary control module, a stability status module, and a supervisory control module. The primary control module is configured to determine at least one control action for at least one of an electronic limited slip differential and an aerodynamic actuator of a vehicle based on a driver command. The stability status module is configured to determine whether at least one component of the vehicle is stable or unstable based on an input from a sensor on the vehicle. The at least one component includes at least one of a vehicle body, a front axle, a rear axle, front wheels, and rear wheels. The supervisory control module is configured to adjust the at least one control action when the at least one component is unstable.

Abstract: A robotic system includes a controller configured to obtain image data from one or more optical sensors and to determine one or more of a location and/or pose of a vehicle component based on the image data. The controller also is configured to determine a model of an external environment of the robotic system based on the image data and to determine tasks to be performed by components of the robotic system to perform maintenance on the vehicle component. The controller also is configured to assign the tasks to the components of the robotic system and to communicate control signals to the components of the robotic system to autonomously control the robotic system to perform the maintenance on the vehicle component.

Abstract: A method for estimating an effective length of a first vehicle segment of a vehicle combination, the vehicle combination comprising a towing vehicle which is connected to the first vehicle segment via a first articulation joint and a perception sensor mounted on one of the towing vehicle and the first vehicle segment and arranged to obtain an image of the other one of the towing vehicle and the first vehicle segment; the method comprising identifying that the vehicle combination is provided in a first steady vehicle state, identifying that a turning and driving manoeuvre is initiated, identifying when the vehicle combination reaches a second steady vehicle state, determining a time period required for driving the vehicle combination from the first steady vehicle state to the second steady vehicle state, and estimating the effective length by use of the time period, the specific angular change, and the specific speed.

Abstract: An information processing method is to be executed by a computer. The information processing method includes: receiving, from an autonomous moving body, a first processing result that is a result of first preprocessing of travel control processing in autonomous movement processing of the autonomous moving body, and sensing data received by the autonomous moving body; executing second preprocessing based on the sensing data to receive a second processing result, the second preprocessing being more advanced than the first preprocessing; determining a difference between the first processing result and the second processing result; and outputting, to the autonomous moving body based on the difference determined, a change request to change the first processing result to the third processing result, the third processing result being received based on at least one of the first processing result or the second processing result.

Abstract: A method, computer program product, and computing system for monitoring the interior of an autonomous vehicle for information being provided by a rider of the autonomous vehicle to the autonomous vehicle; and processing the information provided by the rider of the autonomous vehicle to the autonomous vehicle to generate a response based, at least in part, upon the information provided by the rider of the autonomous vehicle.

Abstract: Methods, systems, and non-transitory computer-readable media are configured to perform operations comprising determining a rescue lane scenario for an environment, determining an amount of lateral bias for a vehicle, and generating planning and control data for the vehicle to laterally bias based on the amount of lateral bias.

Abstract: Embodiments of the invention include a vehicle telematics system including a telematics device and a remote server system, wherein the telematics device obtains sensor data from at least one sensor installed in a vehicle, calculates peak resultant data based on the sensor data, generates crash score data based on the peak resultant data and a set of crash curve data for the vehicle, and provides the obtained sensor data when the crash score data exceeds a crash threshold to the remote server system and the remote server system obtains vehicle sensor data and vehicle identification data from the vehicle telematics device, calculates resultant change data and absolute speed change data based on the obtained sensor data and/or the vehicle identification data, and generates crash occurred data when the resultant change data exceeds a first threshold value and when the absolute speed change data is below a second threshold value.

Abstract: An autonomous running vehicle transmits a camera image around the vehicle photographed by a camera to a remote monitoring center. An obstacle is detected on the basis of information obtained from autonomous sensors including the camera. When an obstacle is detected, the autonomous running vehicle is automatically stopped. The remote monitoring center determines, when the autonomous running vehicle automatically stops, whether or not the run of the autonomous running vehicle is permitted to restart on the basis of the received camera video. When it is determined that the autonomous running vehicle can be restarted, a departure signal is transmitted to the autonomous running vehicle. When the departure signal is received from the remote monitoring center, the autonomous running vehicle restarts running.

Abstract: Techniques are described herein for predicting popularity metrics and/or visitation metrics that are used in the selection of a point of interest (POI) for placement of an electric vehicle charging station (EVCS). The techniques involve training a machine learning model based on information obtained about POIs at which EVCSs are already installed. The information used to train the machine learning model includes, for each existing installation location: (a) visitation data that describes visitation features, and (b) popularity metrics and/or visitation metrics that have been generated for the location. When the machine learning model has been trained, the trained machine learning model predicts popularity metrics and/or visitation metrics for a POI location at which no EVCS has been installed based on the visitation data of that POI.

Abstract: A method for predicting, for a motor vehicle traveling on a first road segment, a future coefficient of friction of the vehicle on a second road segment. The method includes steps of obtaining operating parameters of the vehicle and at least one characteristic of the first road segment, of computing an indicator on the basis of the obtained operating parameters of the vehicle, of determining a frictional category of the vehicle according to the value of the computed indicator and of the at least one obtained characteristic of the road segment, of selecting a friction profile of the vehicle on the basis of the determined frictional category, and of determining a coefficient of friction of the vehicle by applying the selected profile to at least one characteristic of the second road segment. A device for implementing the prediction method is also disclosed.

Abstract: A ship body control device is provided, which includes a control lever having a neutral position, and processing circuitry. When the control lever is moved during an automatic cruise, the processing circuitry executes a deceleration control from a speed of a ship body during the automatic cruise, and when the position of the control lever is in agreement with a position for changing to a manual cruise, the processing circuitry changes the automatic cruise to the manual cruise at a rotating speed of an engine according to the position for changing to the manual cruise.

Abstract: A design method of a high energy efficiency unmanned aerial vehicle (UAV) green data acquisition system belongs to the technical field of data acquisition and optimization for UAV uplink communication. Firstly, a system optimization objective is constructed; and in a uplink communication network of a single UAV and ground sensors, the UAV receives data periodically. Secondly, according to a constructed optimization problem, the optimization objective is maximization of EE({W},{t},{S}). Finally, an original problem is decomposed into two approximate concave-convex fractional sub-problem based on a block coordinate descent method and a successive convex approximation technique to obtain a suboptimal solution; an overall iterative algorithm is proposed: in each iteration, by solving the sub-problems, wake-up scheduling S, time slot t and UAV trajectory W are alternately optimized. The solution obtained in each iteration is used as the input of next iteration.

Abstract: Systems, devices, and methods for receiving, by a processor having addressable memory, data representing a geographical area for imaging by one or more sensors of an aerial vehicle; determining one or more straight-line segments covering the geographical area; determining one or more waypoints located at an end of each determined straight-line segment, where each waypoint comprises a geographical location, an altitude, and a direction of travel; determining one or more turnarounds connecting each of the straight-line segments, where each turnaround comprises one or more connecting segments; and generating, by the processor, a flight plan for the aerial vehicle comprising: the determined one or more straight-line segments and the determined one or more turnarounds connecting each straight-line segment.

Abstract: A method of using perception-inspired event generation for situation awareness for a vehicle, including receiving perception input data from a sensor of the vehicle and processing the perception input data to classify and generate parameters related to an external entity in a vicinity of the vehicle. The method includes generating a hierarchical event structure that classifies and prioritizes the perception input data by classifying the external entity into an attention zone and prioritizing the external entity within the attention zone according to a risk level value for the external entity. A higher risk level value indicates a higher priority within the attention zone. The method further includes developing a behavior plan for the vehicle based on the hierarchical event structure.