Abstract: A pedal fault diagnosis method and apparatus for a vehicle are provided, including: detecting whether a driver seat is in an unmanned state; collecting an actual zero position voltage of a pedal when the driver seat is in the unmanned state; and then determining, based on the actual zero position voltage, whether a zero position fault exists on the pedal. The apparatus may update a set value of a zero position voltage in a vehicle controller based on the actual zero position voltage that is collected when the driver seat is in the unmanned state, and may be applied to the fields of assisted driving and automatic driving. Vehicle control safety can be improved by using the actual zero position voltage that is collected when the driver seat is in the unmanned state.

Abstract: Aspects of the present invention relate to a method of controlling one or more active vanes (2-n) on a host vehicle (VH1) having an energy recovery system (10). The one or more active vanes (2-n) is selectively configurable in a first position and a second position. The method comprises, in respect of one or more current operating parameters of the host vehicle (VH1), determining a first energy expended value (EEV1) and a first energy recovery value (ERV1) associated with the one or more active vanes (2-n) in the first position. A second energy expended value (EEV2) and a second energy recovery value (ERV2) associated with the one or more active vanes (2-n) are determined in respect of the second position. A first difference (D1) is determined between the first energy expended value (EEV1) and the first energy recovery value (ERV1). A second difference (D2) between the second energy expended value (EEV2) is determined and the second energy recovery value (ERV2).

Abstract: A vehicle and a control method thereof may increase a shooting angle of a camera mounted on the vehicle to photograph without limitation of the shooting angle. The method of controlling a vehicle including at least one camera, the control method including: adjusting a direction of a vehicle body to adjust a shooting direction of the at least one camera to a target direction thereof; and controlling the at least one camera to photograph in the adjusted shooting direction.

Abstract: System, methods, and computer-readable media for an object path prediction model, and an associated training technique, to output a path that is considered an object collision path. The object path prediction model outputs a set of predicted paths for the object that are outputted to a trained planning algorithm, which includes paths that are most likely to occur and a path that is considered an object collision path. The predicted paths are sent to the trained planning algorithm and used for planning a trajectory for the autonomous vehicle that is associated with a low probability of colliding with or taking a sudden evasive action to avoid the object.

Abstract: A remote operation terminal of a crane provided with a GNSS receiver for calculating the current position of the tip of a boom: acquires attitude information of the crane and the current position of the tip of the boom from a control device of the crane; generates a three-dimensional image of the crane at the current time and planimetric features on the basis of the information acquired from the control device and three-dimensional information acquired by a three-dimensional information acquisition unit; displays, on a display device, the generated three-dimensional image at the position of and in the direction of a viewpoint input to a viewpoint changing operation tool; and generates a control signal for the crane so that the tip of the boom of the three-dimensional image moves in a moving direction input to a suspended load moving operation tool in the three-dimensional image of the crane displayed on the display device.

Abstract: A method of performing autonomous driving based on platooning by a moving object includes setting a moving path, determining whether platooning is allowed, transmitting moving path information to a first intelligent transportation system infrastructure when the moving object of a plurality of moving objects approaches a preset range of the first intelligent transportation system infrastructure, receiving platooning information from the first intelligent transportation system infrastructure, and performing platooning based on the platooning information, wherein the first intelligent transportation system infrastructure groups ones of the moving objects capable of platooning from among the plurality of moving objects based on the moving path information received from each of the plurality of moving objects.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive radar data including a radar pixel having a radial velocity from a radar; receive camera data including an image frame including camera pixels from a camera; map the radar pixel to the image frame; generate a region of the image frame surrounding the radar pixel; determine association scores for the respective camera pixels in the region; select a first camera pixel of the camera pixels from the region, the first camera pixel having a greatest association score of the association scores; and calculate a full velocity of the radar pixel using the radial velocity of the radar pixel and a first optical flow at the first camera pixel. The association scores indicate a likelihood that the respective camera pixels correspond to a same point in an environment as the radar pixel.

Abstract: An electric vehicle computing sharing system (100) is adapted to receive a signal indicating the electric vehicle (110, 120, 130) is connected to a charging station (115, 125, 135). The computing sharing system (100) may be further adapted to receive information about the electric vehicle (110, 120, 130). The computing sharing system (100) may be further adapted to determine a predicted charging duration (535) for the electric vehicle (110, 120, 130). The computing sharing system (100) may be further adapted to identify a task for execution by a computing resource of the electric vehicle (110, 120, 130) based on the predicted charging duration (535). The computing sharing system (100) may be further adapted to transmit the task to the electric vehicle (110, 120, 130). The computing sharing system (100) may be further adapted to receive a result for the task from the electric vehicle (110, 120, 130).

Abstract: The invention relates to a self-moving device, including: a housing, a movement module configured to drive the housing to move, a drive module configured to drive the movement module to move, and a control module configured to control the self-moving device. A non-contact obstacle recognition sensor assembly is disposed on the housing. After the obstacle recognition sensor assembly detects that an obstacle exists in a movement direction, the control module controls the self-moving device to continue moving and steer until the obstacle is avoided. The movement direction is a forward driving direction of the self-moving device.

Abstract: An interference margin between a stator and a rotor is measured after a rotary electric machine is manufactured, and the measured value is stored in a memory of a life predicting device as an allowable limit value. The life predicting device calculates a wear amount of a bearing portion of the rotary electric machine from an operation state amount of the rotary electric machine, and determines whether or not the rotary electric machine reaches an end of a life and maintenance is needed based on the calculated value and the allowable limit value stored in the memory.

Abstract: An information processing apparatus includes a communication interface configured to communicate with a first unmanned aircraft having a first camera to be used for detecting an obstacle and a second unmanned aircraft having a second camera to be used for detecting an obstacle with higher detection accuracy than the first camera, and a controller configured to, in a case in which a predetermined event relating to the first unmanned aircraft has occurred, detect, using the second unmanned aircraft, an obstacle at a target point on a flight path along which the first unmanned aircraft travels to a destination, and control the first unmanned aircraft to navigate around the detected obstacle using information regarding the detected obstacle.

Abstract: A method for determining a movement vector of a motor vehicle includes: determining, via a radar system of the vehicle, at two successive instants, positions, relative to the vehicle, of elements of an environment of the vehicle that are static relative to the environment, associating the positions determined at these two successive instants with each other in such a way as to form different pairs of positions each grouping together the preceding position and the subsequent position of a given element of the environment, and determining the movement vector of the vehicle by linear regression, based on the pairs of positions thus formed.

Abstract: In a system for controlling a watercraft, when a first mode is selected, a controller determines a route on which a single or a plurality of specified spots including a destination are located, and controls a marine propulsion device such that the watercraft moves along the route with a bow thereof being kept oriented in a predetermined cardinal direction. When a second mode is selected, the controller controls the marine propulsion device such that the bow of the watercraft is kept oriented in the predetermined cardinal direction without determining the route. The controller obtains a position of the watercraft. In the first mode, the controller determines whether or not the watercraft has passed through the destination. When the watercraft has passed through the destination in the first mode, the controller performs a mode switching from the first mode to the second mode and controls the marine propulsion device in the second mode.

Abstract: Techniques for utilizing a depth completion algorithm to determine dense depth data are discussed are discussed herein. Two-dimensional image data representing an environment can be captured or otherwise received. Depth data representing the environment can be captured or otherwise received. The depth data can be projected into the image data and processed using the depth completion algorithm. The depth completion algorithm can be utilized to determine the dense depth values based on intensity values of pixels, and other depth values. A vehicle can be controlled based on the determined depth values.

Abstract: Autonomous vehicle methods and systems are described herein for communicating with an autonomous or semi-autonomous vehicle to remotely control operation of the vehicle, to detect and remove unauthorized passengers, to deliver loads, to receive registration information for the vehicle, to provide accessibility information to the vehicle, and/or to receive sensor or other environmental data to integrate with an electronic game or other extended reality experience.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for drone-assisted thermal monitoring. One of the methods includes determining a first temperature measurement at a first location of a property, navigating from the first location to a second location of the property, determining a second temperature measurement at the second location, generating a thermal model for the property based on the first temperature measurement and the second temperature measurement, and providing the thermal model for output.

Abstract: An installation error of a machine-body inertial measurement unit around a first axis is computed on a basis of sensing results of inertial measurement units of a front work implement, and the machine-body inertial measurement unit obtained while the upper swing structure is in a first calibration posture in which the upper swing structure faces a predetermined direction relative to a lower travel structure; and an installation error of the machine-body inertial measurement unit around a second axis is computed on a basis of a sensing result of the machine-body inertial measurement unit obtained while the upper swing structure is in a second calibration posture in which the upper swing structure is swung by 90 degrees relative to the lower travel structure from the first calibration posture, and the installation error of the machine-body inertial measurement unit around the first axis.

Abstract: A survey system includes a controller storing a map comprising a plurality of nodes representing data capture points of the environment. The controller is configured to segment the plurality of nodes into a plurality of communities, where each community from among the plurality of communities includes a set of nodes from among the plurality of nodes. The controller is configured to generate, for each community from among the plurality of communities, one or more traversability scores. The controller is configured to assign, for each community from among the plurality of communities, at least one robot from among a plurality of robots to survey the community based on the one or more traversability scores. The controller is configured to deploy, for each community from among the plurality of communities, at least one of the plurality of robots based on the plurality of robots assigned to the community.

Abstract: Methods and systems for unmanned aerial vehicles are provided. One method includes receiving, by a control system, sensor data from a mobile ground-based platform and sensor data from a ground-based radar surveillance system, the control system configured to communicate with a first UAV and a second UAV; detecting, by the control system, an object likely to impede the second UAV flight within a flight path, the object detected based on the sensor data received from the mobile ground-based platform, the ground-based radar surveillance system or both the ground-based radar surveillance system and the mobile ground-based platform; generating, by the control system, an indicator indicating an object in the flight path; and transmitting, by the control system, the indicator to the first UAV.

Abstract: Disclosed herein are embodiments for providing contingency automation to emergency response. One embodiment of a method includes determining a route for a vehicle to a primary destination, and determining a first upcoming area along the route that has been previously identified as an emergency response zone, where the emergency response zone may be used as a secondary destination in a contingency route for the vehicle in an emergency. In some embodiments, the method may include reserving airspace for the contingency route, determining that the emergency response zone is no longer useful, based on an updated position of the vehicle, and canceling the contingency route from reservation.