A system and method for calibrating a vehicle optical sensor includes positioning the vehicle in a test station having a projection surface in view of the optical sensor, positioning targets on two hubs of the vehicle, and positioning lasers left to right that are mounted on a graduated mounting bar in front of the vehicle. The graduated mounting bar includes gradations indicative of a lateral position of the lasers on the graduated mounting bar. The lasers are configured to obtain a distance to the targets and distances along respective axes and between the lasers. The calibration is performed based on the obtained distances and once the vehicle's position in the test station is known with respect to the test station.

Perception sensors of a vehicle can be used for various operating functions of the vehicle. A computing device may receive sensor data from the perception sensors, and may calibrate the perception sensors using the sensor data, to enable effective operation of the vehicle. To calibrate the sensors, the computing device may project the sensor data into a voxel space, and determine a voxel score comprising an occupancy score and a residual value for each voxel. The computing device may then adjust an estimated position and/or orientation of the sensors, and associated sensor data, from at least one perception sensor to minimize the voxel score. The computing device may calibrate the sensor using the adjustments corresponding to the minimized voxel score. Additionally, the computing device may be configured to calculate an error in a position associated with the vehicle by calibrating data corresponding to a same point captured at different times.

Methods and devices for determining axis of symmetry of self-driving vehicle (SDV) and for calibrating a Light Detection and Ranging (LIDAR) system are disclosed. One of the axes of the system of coordinates of the LIDAR system extends along a normal direction of a ground surface. the method includes acquiring a subset of detected points in the system of coordinates; generating a subset of mirror-image points based on the subset of detected points; projecting the subset of mirror-image points onto the subset of detected points so as to define pairs of overlapping data points; using symmetrically opposite detected points for determining the axis of symmetry of the SDV in the system of coordinates of the LIDAR system; and calibrating the LIDAR system using an angular offset between the axis of symmetry of the SDV and an other one of the axes of the system of coordinates of the LIDAR system.

A machine-vision vehicle service system, and methods of operation, incorporating at least one at least one camera and an optical projector for guiding placement of vehicle service components relative to a vehicle undergoing service. The camera and optical projector are operatively coupled to a processing system configured with software instructions to selectively control a projection axis orientation for the optical projector to enable projection of visible indicia onto various surfaces visible within the field of view of the camera.

An orientation-position determining device is provided which is used for a sensor installed in a vehicle. The orientation-position determining device includes an imaging unit and an orientation-position detector. The imaging unit works to obtain a ranging image and an ambient light image from the sensor. The ranging image represents a distance to a target lying in a light emission region to which light is emitted from the sensor. The ambient light image represents an intensity of ambient light and has a resolution higher than that of the ranging image. The orientation-position detector works to use the ranging image and the ambient light image to detect an orientation and/or a position of the sensor.

An optical detection apparatus is provided. The optical detection apparatus includes a light emitting unit, a light receiving unit, a storage unit, and a determining unit. The light emitting unit includes a plurality of light-emitting elements. The light receiving unit includes a light-receiving element arrayformed by a plurality of light-receiving pixels, which receive reflected light corresponding to emitted light of the light emitting unit. The storage unit stores a reference light-receiving region on the light-receiving element array corresponding to a location of occurrence of light intensity unevenness included in the emitted light of the light emitting unit. The determining unit determines an optical axis misalignment using a positional displacement between the reference light-receiving region and a detected light-receiving region of light intensity unevenness included in the reflected light of the emitted light on the light-receiving element array.

A LIDAR-to-LIDAR alignment system includes a memory and an autonomous driving module. The memory stores first and second points based on outputs of first and second LIDAR sensors. The autonomous driving module performs a validation process to determine whether alignment of the LIDAR sensors satisfy an alignment condition. The validation process includes: aggregating the first and second points in a vehicle coordinate system to provide aggregated LIDAR points; based on the aggregated LIDAR points, performing (i) a first method including determining pitch and roll differences between the first and second LIDAR sensors, (ii) a second method including determining a yaw difference between the first and second LIDAR sensors, or (iii) point cloud registration to determine rotation and translation differences between the first and second LIDAR sensors; and based on results of the first method, the second method or the point cloud registration, determining whether the alignment condition is satisfied.

A self-calibrating scanning system and method provides a novel way to eliminate errors in scanning systems, such as lidar or radar detection, using an inertial measurement unit. The system includes an energy transmission source configured to transmit an energy signal through a transmittal area. A detector receives a return energy signal of at least one target object of the energy transmitter source within the transmittal area. The system calculates at least one of the range and position of an object from information relating to at least one of the time and phase of the return energy signal relative to the transmittal energy signal. The spatial or angular displacement of the detector relative to the light source is measured using data from the inertial measurement unit, and at least one of calculated range and position of the object is adjusted based on the spatial or angular displacement of the detector.

A sensor calibration method and apparatus, and a storage medium are provided. In the method, multiple scene images and multiple first point clouds of a target scene are acquired by an image sensor and a radar sensor. A second point cloud of the target scene is constructed according to the multiple scene images. A first distance error between the image sensor and radar sensor is determined according to first feature point sets and a second feature point set. A second distance error of the radar sensor is determined according to multiple first feature point sets. A reprojection error of the image sensor is determined according to a first global position of the second feature point set in the global coordinate system and first image positions of pixel points corresponding to the second feature point set in the scene image. The radar sensor and image sensor are calibrated.

A distance measurement device includes a light-emitting-unit that emits irradiation light toward an object; a light-receiving unit that receives reflected light from the object; a distance-calculation unit that calculates a distance to the object based on a transmission time of the reflected light received; a posture-adjustment mechanism that adjusts a posture of at least the light-receiving-unit; and a posture-controller that drives the posture-adjustment mechanism. The light-receiving unit is formed of a two-dimensional sensor in which a plurality of pixels are two-dimensionally arrayed, and the distance-calculation unit calculates two-dimensional distance data from received light data in each of the pixels of the two-dimensional sensor. The posture-controller controls the posture of the light-receiving unit via the posture-adjustment mechanism such that a direction of a pixel array of the two-dimensional sensor is inclined by a predetermined angle θ with respect to a direction of a ridge of the object to receive the light.