Abstract: Described is a method for aligning a vehicle service system (1) relative to a vehicle (2) positioned in a service area (8), where the vehicle service system (1) comprises: a calibration structure (3) for calibrating an ADAS sensor of an advanced driver assistance system of the vehicle (2); an apparatus (4) for measuring the alignment of the vehicle (2) and on which an apparatus camera (41) is mounted; wherein the method comprises the following steps: applying a front wheel target (51) and a rear wheel target (52) on a front wheel and on a rear wheel of the vehicle (2); capturing an image through the apparatus camera (41), wherein the image represents the front wheel target (51) and the rear wheel target (52); processing the image to derive information useful for positioning the calibration structure (3) relative to the vehicle (2); placing a positioning device (7) at an operating position, spaced from the calibration structure (3), in front of the apparatus (4) and alongside the first side of the vehicle (2).

Abstract: The present technology relates to a control device, a control method, an unmanned aircraft, an information processing device, an information processing method, and a program capable of reflecting the user's intentions and reducing damage in the event of a failure in an unmanned aircraft. A control device of a first aspect of the present technology is a device that controls movement of an unmanned aircraft during a fall according to a control command generated for an image showing a falling position, captured by the unmanned aircraft. The present technology can be applied to a device that controls a drone that controls movement so as to shift the falling position when an aircraft fails.

Abstract: A speed determination method, an electronic device and a computer storage medium are provided, relates to the field of computer technology, and may be applied to the field of artificial intelligence, especially the field of automated driving. The method includes: determining an expected speed direction of a controlled point of a first controlled target according to an actual location of the controlled point of the first controlled target and a preset trajectory of the controlled point of the first controlled target, wherein the first controlled target is one of a plurality of controlled targets having a kinematic relationship; and determining a target speed of at least one controlled target of the plurality of controlled targets according to the expected speed direction of the controlled point of the first controlled target and the kinematic relationship.

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: The present application relates to a multi-sensor-fusion-based autonomous mobile robot indoor and outdoor navigation method and a robot. The method includes: acquiring inertial measurement data and three-dimensional point cloud data of a robot at a current position; determining a pose change of the robot based on the inertial measurement data of the robot at the current position; performing distortion correction on the three-dimensional point cloud data of the robot at the current position based on the pose change of the robot; and matching the three-dimensional point cloud data after the distortion correction with a navigation map, to determine the current position of the robot. With the method, the robot can be accurately positioned.

Abstract: The present disclosure is an autonomous robotic cargo system for moving and accurately positioning cargo inside an aircraft or at any other designated location in an austere environment. The system has a chassis coupled to one or more tracks for moving the chassis from a first location to a second location. The chassis is also coupled to one or more forks for loading cargo and unloading the cargo. In addition, the chassis has a laser scanner positioned on the chassis to capture data indicative of the chassis' environment. The system further has a control processor that pre-generates a preliminary pathway for the chassis to travel from the first location to the second location based upon laser scanner data received from the laser scanner. The control processor also controls the one or more forks to pick up cargo and controls the one or more tracks to move the cargo from the first location to the second location.

Abstract: A computerized method of performing safety and functional verification of algorithms, for control of autonomous vehicles, comprises: iteratively performing an adjustment, the adjustment comprising at least one of the following: (i) updating the value of parameter(s) indicative of noise and/or delay in simulated sensor(s), associated with a computerized simulation framework corresponding to simulated autonomous vehicle(s) and to operational environment(s), by increasing noise and/or delay; and (ii) updating the value of parameter(s) indicative of noise and/or delay in a response of the simulated autonomous vehicle(s) to command(s), by increasing the noise and/or delay. This is done until obtaining from the computerized simulation framework an increased-severity computerized simulation framework. The increased-severity computerized simulation framework meets a criterion that can be utilized for statistical safety verification and/or statistical functional performance verification of the algorithm(s).

Abstract: An electronic device is provided. The electronic device includes a first device comprising a spherical housing which rotates and in which a spherical inner space is formed, and a second device which is disposed on the outer surface of the spherical housing and has a ring shape, wherein the first device comprises a first driving device which is disposed within the spherical housing and is capable of transmitting driving force to the spherical housing, a structure disposed within the spherical housing and formed such that the second device is disposed on the surface of the spherical housing, a second driving device which is disposed within the spherical housing and drives the structure, and at least one first sensor which is disposed in the structure and faces the inner surface of the spherical housing.

Abstract: A server device includes a communication unit and a control unit that sends and receives information to and from another device via the communication unit. The control unit sends, to a terminal device, information on a comfort level in a vehicle cabin of a shared vehicle that is determined based on a detection result of detecting an effect of a passenger on a vehicle body or equipment of the shared vehicle to present the information to another passenger before boarding the shared vehicle.

Abstract: A control apparatus includes a controller configured to acquire route information indicating a route on which a user is to travel, and travel information indicating a travel status of the user, detect, based on the acquired route information and the acquired travel information, a waiting point on the route, at which a waiting time period for the user is to occur, and output deceleration information for prompting the user to decelerate to delay, within a range of the waiting time period, arrival of the user at the detected waiting point.

Abstract: A method, a computer program, an apparatus, a transportation vehicle, and a network entity for predicting a deadlock situation for an automated transportation vehicle. The deadlock situation is an exceptional traffic situation necessitating a change of an operational mode of the transportation vehicle. The method for predicting a deadlock situation for the automated transportation vehicle includes obtaining information related to a historical deadlock situation cause, determining historical context information for the historical deadlock situation cause, determining information indicative for the deadlock situation cause based on the information related to the historical context information, monitoring actual context information for information indicative for the deadlock situation, and predicting the deadlock situation based on the information indicative for the deadlock situation in the actual context information.

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: Systems and methods for a computer-based process that optimizes vehicle fleet charging systems. Failed chargers are detected and optimal paths are determined between these failed chargers and available chargers. Upon determining the optimal path, instructions to route the vehicle from the failed chargers to available chargers via these shortest paths are then communicated.

Abstract: A 3D map comprising sensor data items depicting the environment is updated, each sensor data item having one or more associated variables such as a pose of a capture device or a position of a landmark. A graph is calculated from sensor data items. The graph comprises nodes and edges, a node representing at least one variable in the received sensor data items and an edge representing relationships between variables. The graph is partitioned into a plurality of subgraphs so as to reduce a number of variables that are shared between subgraphs. Each of the plurality of subgraphs is allocated to a respective worker node. At each worker node, updated values of the variables are computed. The process updates values of variables which are shared between subgraphs to a common value using a consensus process. The 3D map of the environment is updated according to the updated values of the variables.

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: Disclosed embodiments include systems, vehicles, and methods for tracking off-road travel. In an illustrative embodiment, a system includes a computing device having computer-readable media storing computer-executable instructions configured to cause the computing device to monitor a vehicle location. The vehicle location is identified on map data for an area encompassing the location and including road data for recognized roads in the area. Off-road travel is detected in response to determining that the vehicle location is outside of the recognized roads. Travel data is recorded representing the off-road travel of the vehicle.

Abstract: A map generation device is configured to determine evaluation value of each of a plurality of evaluation items that serve as indices for evaluation the reliability of the positional information of the planimetric feature. The plurality of evaluation items include any of an error amount when arrangement of composing points of the planimetric feature is approximated, a parallelism between an arrangement direction of composing points of the planimetric feature and a movement trajectory of the measuring vehicle, a distance between a position indicated by the position information of the planimetric feature and a position of the measuring vehicle when the position of the planimetric feature is measured, an absolute value of reflection intensity of a position of the planimetric feature obtained from the measurement information or a difference between a position of the planimetric feature and surrounding reflection intensity of the planimetric feature, and so on.

Abstract: A method for following a person associated with a vehicle, the method may include entering a tracking mode for following the person; when operating in the tracking mode performing at least one out of: autonomously driving an autonomous vehicle towards the person and parking in proximity to the person, and autonomously driving towards the person and picking up the person.

Abstract: An apparatus and method for monitoring the status and health of a fleet of vehicles operating in a common space. A centralized monitoring operator receives status information and has the capability to independently interact with each vehicle in the fleet.

Abstract: There is provided a vehicle and method for projecting a light pattern. The method comprises: projecting a light pattern to match a footprint of an object, wherein the object is associated with a vehicle and is moveable relative to the vehicle, and wherein the footprint is indicative of an area that the object is or will be occupying. The method further comprises modifying the projected light pattern based on a state of the object.