Abstract: A vehicle motion control device generates a travel route where behavior of a vehicle traveling on a curve is small and comfortable ride is achieved even when the vehicle travels on a continuous curve. The control device includes a travel track generation unit that generates, based on information on a curvature of a first curve on a lane existing in a traveling direction of a vehicle and a curvature of a second curve connected to the first curve, a travel route by setting curvature of the travel route at a time of traveling on a curve having a smaller curvature between the first and second curves to be larger than the curvature of the curve and setting a curvature of the travel route at a time of traveling on a curve having a larger curvature between the first and second curves to be smaller than the curvature of the curve.

Abstract: A method, a computer program comprising instructions, and a device for processing sensor data in a motor vehicle. An assistance system for a motor vehicle in which a method is implemented, and a motor vehicle having such a system. Sensor data is received. At least one algorithm is applied to the sensor data to determine a first intermediate result. At least one rule is applied to the first intermediate result to determine a second intermediate result. The second intermediate result is evaluated with regard to plausibility. If the second intermediate result is implausible, one or more of the rules applied to the first intermediate result is reversed until the second intermediate result is plausible. The second intermediate result thereby obtained is finally output as an end result.

Abstract: A method for controlling an automated driving operation includes setting up respective independent models for executing planning and learning in the automated driving operation, including a vehicle planning model and a cognitive learning model. A semantic layer is generated to act as a bridge between the cognitive learning model and the vehicle planning model, the semantic layer including a first data adaptor and a second data adaptor. The method includes transforming real traffic data to a respective equivalent abstract representation such that it can be used by the cognitive learning model to generate a humanized reward model, via the first data adaptor. The method includes determining a trajectory plan, via the vehicle planning model, based in part on the humanized reward model. The vehicle has a controller that executes the automated driving operation based in part on the trajectory plan.

Abstract: A mobile object control method including: recognizing physical objects near a mobile object and a route shape; generating a target trajectory based on a result of the recognition; causing the mobile object to travel autonomously along the target trajectory; and determining that an abnormality has occurred in a control system for causing the mobile object to travel autonomously by performing the recognition when a degree of deviation between a reference target trajectory determined by the route shape and serving as a reference for generating the target trajectory and the target trajectory is greater than or equal to a first reference degree and output a determination result.

Abstract: Techniques are disclosed that enable training a meta-learning model, for use in causing a robot to perform a task, using imitation learning as well as reinforcement learning. Some implementations relate to training the meta-learning model using imitation learning based on one or more human guided demonstrations of the task. Additional or alternative implementations relate to training the meta-learning model using reinforcement learning based on trials of the robot attempting to perform the task. Further implementations relate to using the trained meta-learning model to few shot (or one shot) learn a new task based on a human guided demonstration of the new task.

Abstract: Disclosed are Ethernet-based vehicle control system and method. The system includes: a router for connecting a vehicle internal network and a vehicle external network when the vehicle internal network is formed by connecting an engine and a vehicle electronic element including a controller and a sensor; and a remote start module for performing remote start based on a remote start signal transmitted from a remote controller through the vehicle external network, wherein whether or not to perform the remote start is determined based on drive system state information generated by the vehicle electronic element and transferred via the router. When performing a remote start is controlled in response to an engine RPM during the remote start, efficient management of engine protection and fuel consumption can be achieved. When performing a remote start is controlled in response to the position of the transmission, safe remote start can be achieved.

Abstract: A short-circuiting device according includes a short circuit that is electrically connected to a robot, the robot including a robotic arm and at least one motor, the robotic arm including at least one joint shaft that is provided with the respective at least one motor, the short circuit being provided separately from a robot controller configured to control the robot, the short circuit being configured to apply a dynamic brake to each motor.

Abstract: A device may receive emergency data, traffic data, network performance data, crime data, and gunshot data associated with a geographical area and may identify a location within the geographical area based on the emergency data, the traffic data, the network performance data, the crime data, and the gunshot data. The device may determine, based on the emergency data, the traffic data, the network performance data, the crime data, and the gunshot data for the location, a risk level for the location and may identify an autonomous vehicle based on the risk level, the traffic data, and the network performance data for the location. The device may determine a route for the autonomous vehicle to the location based on the traffic data and the network performance data for the location, and may perform actions based on the autonomous vehicle and the route.

Abstract: Described herein is a visual indication system implemented on a mobile machine. The visual indication system at least partially surrounds the mobile machine and includes a plurality of displayable regions. Objects surrounding the mobile machine are detected using an object detection sensor. A direction with respect to the mobile machine is detected for each of the objects. A current state of the mobile machine is determined. An object-directed indicator for each of the objects is generated based on the current state of the mobile machine. The object-directed indicator for each of the objects is displayed on the visual indication system at a particular displayable region based on the direction of the particular object.

Abstract: The present disclosure provides a controller for controlling an ego vehicle in an uncertain environment. The controller is caused to acquire knowledge of the environment from measurements associated with sensors the ego. The measurements are based on a state of the ego vehicle and sensing instructions associated with controlling an operation of the sensors. The controller is further caused to estimate a state of the environment, including uncertainty of a state of the at least one moving object or obstacle in the environment. Further a sequence of control inputs is determined by solving a multivariable and a multistage stochastic constrained optimization of a model of the motion of the ego vehicle. The controller is then caused to control the ego vehicle and the sensors based on the sequence of control inputs and the sequence of sensing instructions.

Abstract: Among other things, we describe techniques for detecting objects in the environment surrounding a vehicle. A computer system is configured to receive a set of measurements from a sensor of a vehicle. The set of measurements includes a plurality of data points that represent a plurality of objects in a 3D space surrounding the vehicle. The system divides the 3D space into a plurality of pillars. The system then assigns each data point of the plurality of data points to a pillar in the plurality of pillars. The system generates a pseudo-image based on the plurality of pillars. The pseudo-image includes, for each pillar of the plurality of pillars, a corresponding feature representation of data points assigned to the pillar. The system detects the plurality of objects based on an analysis of the pseudo-image. The system then operates the vehicle based upon the detecting of the objects.

Abstract: System, methods, and other embodiments described herein relate to skid recovery for a vehicle. In one embodiment, a method for controlling a vehicle during skid includes obtaining data indicating a skid condition of the vehicle, determining whether the skid condition can be corrected by counter-steering, and executing an intervention when the skid condition cannot be corrected by counter-steering, the intervention including inducing slippage in front wheels of the vehicle to change a direction and/or magnitude of lateral forces at the front wheels.

Abstract: Systems and methods described in this disclosure provide methods and systems for automatic deployment of a vehicle covering apparatus to protect the vehicle from environmental conditions such as severe weather.

Abstract: A processor is operably coupled to a time of flight (TOF) camera, a light detection and ranging (LIDAR) sensor, and an optical camera. The processor can receive a TOF signal representative of a first coordinate associated with a stick-up height of a tool joint of a pipe of a drill string during a tripping operation on a rig drill floor, and a pitch and a roll of the tool joint. The processor can receive a LIDAR signal representative of a second coordinate associated with the stick-up height, and the pitch of the tool joint. The processor can receive an optical camera signal representative of a third coordinate associated with the stick-up height of the tool joint and the roll of the tool joint. The processor can generate a pose estimate and an orientation estimate based on the signals.

Abstract: A control system for a vehicle comprises a controller comprising a processor and a non-transitory computer-readable medium including instructions. The system comprises first, second, and third inputs configured to be manipulated by an operator. The system comprises first, second, and third displays adjacent the first, second, and third inputs, respectively. The first, second and third displays are configured to show first, second, and third indicia, respectively. Manipulation of the first input by the operator transmits a selection input signal to the controller. The controller receives the selection input signal. The processor compares the selection input signal to the instructions in the non-transitory computer-readable medium, transmits a selection output signal to the second and third displays, removes the second and third indicia from the second and third displays, and shows a first sub-selection indicium on the second display and a second sub-selection indicium on the third display.

Abstract: Example implementations may relate to determining a strategy for a drop process associated with a light detection and ranging (LIDAR) device. In particular, the LIDAR device could emit light pulses and detect return light pulses, and could generate a set of data points representative of the detected return light pulses. The drop process could involve a computing system discarding data point(s) of the set and/or preventing emission of light pulse(s) by the LIDAR device. Accordingly, the computing system could detect a trigger to engage in the drop process, and may responsively (i) use information associated with the environment around the vehicle, operation of the vehicle, and/or operation of the LIDAR device as a basis to determine the strategy for the drop process, and (ii) engage in the drop process in accordance with the determined strategy.

Abstract: Systems, methods, and other embodiments described herein relate to improving trajectory forecasting in a device. In one embodiment, a method includes, in response to receiving sensor data about a surrounding environment of the device, identifying an object from the sensor data that is present in the surrounding environment. The method includes determining category probabilities for the object, the category probabilities indicating semantic classes for classifying the object and probabilities that the object belongs to the semantic classes. The method includes forecasting trajectories for the object based, at least in part, on the category probabilities and the sensor data. The method includes controlling the device according to the trajectories.

Abstract: A method for predicting a trajectory of a target vehicle in an environment of a vehicle. The method includes the steps of a) capturing states of the target vehicle, capturing states of further vehicle objects in the environment of the vehicle and capturing road markings by a camera-based capture device; b) preprocessing the data obtained in step a), wherein outliers are removed and missing states are calculated; c) calculating an estimated trajectory by a physical model on the basis of the data preprocessed in step b); d) calculating a driver-behavior-based trajectory on the basis of the data preprocessed in step b); and e) combining the trajectories calculated in steps c) and d) to form a predicted trajectory of the target vehicle.

Abstract: The invention relates to an autonomous underwater vehicle (AUV). The AUV includes a frame and tunnel thrusters for propelling and orientating the AUV, where the tunnel thrusters have inlets and outlets, each of outlets being directed in a different orientation, and are mounted to the frame. The AUV further includes fasteners for connecting the frame to a hull, where the fasteners have an orientation that is substantially parallel to the tunnel thrusters. The hull has a substantially spherical shape and further includes (1) a bottom plate with inlet openings, (2) a top plate with outlet openings, where the top plate and the bottom plate are affixed to the fasteners and hold plate rings of the hull in place, and (3) each of the plate rings that further includes a corresponding retention ring and corresponding central plates.

Abstract: This provides a system and method for handling the interchange of trailers between an over the road (OTR) truck and an autonomous vehicle (AV) yard truck in a facility yard includes an interchange zone (IZ) that is bounded by a predetermined boundary structure, having an OTR entry gate and an OTR exit gate on a first side and an AV entry gate and an AV exit gate on a second side. The system and method further includes a management process that selectively opens and closes each of the OTR entry gate, the OTR exit gate, the AV entry gate and the AV exit gate according to a predetermined set of rules.