A LiDAR sensor (41) is configured to sense information of an outside of a vehicle. An ultrasonic sensor (42) is configured to sense information of the outside of the vehicle in a different manner from the LiDAR sensor (41). A first bracket (43) supports the LiDAR sensor (41) and the ultrasonic sensor (42). A first sensor actuator (44) is configured to adjust a sensing reference position of the LiDAR sensor (41) relative to the first bracket (43). A second sensor actuator (45) is configured to adjust a sensing reference position of the ultrasonic sensor (42) relative to first bracket (43). A first bracket actuator (46) is configured to adjust at least one of a position and a posture of the first bracket (43) relative to the vehicle.

A left front camera (11) is adapted to be mounted on a left front lamp (1LF) of a vehicle to obtain external information of at least ahead of the vehicle. A right front LiDAR sensor (12), a type of which is different from the camera (11), is adapted to be mounted on a right front lamp (1RF) of the vehicle to obtain external information of at least ahead of the vehicle.

An excavator system for locating an underground utility line, the system comprising: a signal transmitter installed on the excavator; a signal receiver installed on the excavator; a monitor; and a control unit, in communication with the receiver, wherein the control unit is adapted (a) to analyze a vicinity of the receiver from the underground utility line by an intensity of a received signal by the receiver, and (b) to display indication of the vicinity on the monitor.

A light detection and ranging system is provided. The system includes a Galvanometer mirror; a multiple-facet light steering device; and a controller device comprising one or more processors, memory, and processor-executable instructions stored in memory. The processor-executable instructions comprise instructions for receiving a first movement profile of the Galvanometer mirror of the LiDAR scanning system; receiving calibration data of the multiple-facet light steering device of the LiDAR scanning system; generating a second movement profile of the Galvanometer mirror based on the calibration data and the first movement profile; and providing one or more control signals to adjust movement of the Galvanometer mirror based on the second movement profile.

A computer-implemented method and device for mapping a vehicle environment of a vehicle are disclosed. The method comprises determining an occupancy grid representing the vehicle environment, including occupancy probability information of a first set of object detections. The occupancy probability information is determined from first positioning information obtained from a first sensor system. Semantic information and second positioning information associated with the semantic information from one or more semantic information sources is obtained. The semantic information comprises object classification information of a second set of object detections and the second positioning system indicates one or more positions of the second set of object detections with respect to the vehicle. The object classification information of the second set of object detections is combined with the occupancy probability information of the occupancy grid to generate a classified occupancy grid.

An orientation control system for an agricultural implement includes a first sensor configured to be positioned at a left end portion of a frame. The first sensor is configured to emit a first output signal toward a soil surface and to receive a first return signal indicative of a first height of the left end portion. The orientation control system also includes a second sensor configured to be positioned at a right end portion of the frame. The second sensor is configured to emit a second output signal toward the soil surface and to receive a second return signal indicative of a second height of the right end portion. In addition, the orientation control system includes a controller configured to control first, second, and third actuators such that a difference between the first height and the second height is less than a threshold value.

Systems and methods for assigning a lane to an object in an environment of an autonomous vehicle are disclosed. The methods include assigning an instantaneous probability to each of a plurality of lanes in the environment based on a current state of the object, generating a transition matrix for each of the plurality of lanes, and identifying the lane in which the object is moving at the current time t based on the instantaneous probability and the transition matrix. The instantaneous probability is a measure of likelihood that the object is in that lane at a current time. The transition matrix encodes one or more probabilities that the object transitioned either into that lane or out of that lane at the current time.

The technology relates to determining general weather conditions affecting the roadway around a vehicle, and how such conditions may impact driving and route planning for the vehicle when operating in an autonomous mode. For instance, the on-board sensor system may detect whether the road is generally icy as opposed to a small ice patch on a specific portion of the road surface. The system may also evaluate specific driving actions taken by the vehicle and/or other nearby vehicles. Based on such information, the vehicle's control system is able to use the resultant information to select an appropriate braking level or braking strategy. As a result, the system can detect and respond to different levels of adverse weather conditions. The on-board computer system may share road condition information with nearby vehicles and with remote assistance, so that it may be employed with broader fleet planning operations.

Provided are systems and methods for a deep learning based beam control. Sensor data associated with the environment and the corresponding detected objects from a perception system are obtained. Object features and image features are extracted. The extracted object features and image features are fused into fused features. A beam control status is predicted according to the fused features, wherein the beam control status indicates a high beam illumination intensity or a low beam illumination intensity of a light emitting device.

A sensor calibration system for calibrating a sensor system associated with a device under test and methods for making and using same. The sensor calibration system can include a turntable system for supporting and rotating the device under test relative to at least one calibration target system and one or more imaging systems distributed about a periphery of the turntable system. The calibration target system can comprise a calibration target device with calibration indicia and a calibration target positioning system for positioning the calibration target device relative to the sensor system; whereas, the imaging systems can capture an image of the device under test as the turntable system rotates the device under test. In selected embodiments, the calibration target system advantageously can calibrate sensor systems that support one or more Advanced Driver Assistance (ADAS) and Autonomous Vehicle (AV) applications when the sensor systems are associated with a passenger vehicle.