A vehicular collision avoidance system comprising a system controller, pulsed laser transmitter, a number of independent ladar sensor units, a cabling infrastructure, internal memory, a scene processor, and a data communications port is presented herein. The described invention is capable of developing a 3-D scene, and object data for targets within the scene, from multiple ladar sensor units coupled to centralized LADAR-based Collision Avoidance System (CAS). Key LADAR elements are embedded within standard headlamp and taillight assemblies. Articulating LADAR sensors cover terrain coming into view around a curve, at the crest of a hill, or at the bottom of a dip. A central laser transmitter may be split into multiple optical outputs and guided through fibers to illuminate portions of the 360° field of view surrounding the vehicle. These fibers may also serve as amplifiers to increase the optical intensity provided by a single master laser.

A method and an apparatus for calibrating a parameter of a laser radar are provided. The cost function used to determine the predicted value of the first parameter is determined based on the three-dimensional coordinates of the sampling points and the fitting function for the sampling points. The fitting function for the plurality of sampling points uses the first parameter as an independent variable.

A method for calibrating a sensor unit disposed on a load-bearing device of an industrial truck includes the steps of: determining a first position of the sensor unit relative to an object located remotely from the industrial truck, displacing the sensor relative to the object in a first direction by a first distance, determining a second position of the sensor unit relative to the object, determining the spatial position or arrangement of the sensor unit relative to the load-bearing device based on the first and second positions, the direction of movement, and the distance between the first and second positions.

Provided are systems and methods for auto calibrating a vehicle using a calibration target that is generated from the vehicle's sensor data. In one example, the method may include receiving sensor data associated with a road captured by one or more sensors of a vehicle, identifying lane line data points within the sensor data, generating a representation which includes positions of a plurality of lane lines of the road based on the identified lane line data points, and adjusting a calibration parameter of a sensor from among the one or more sensors of the vehicle based on the representation of the plurality of lane lines.

Provided are systems and methods for detecting a vehicle with sensors that are not calibrated properly and calibrating such sensor in real-time. In one example, a method may include iteratively capturing sensor data of a road while the vehicle is travelling on the road; monitoring a calibration of the sensors of the vehicle based on the sensor data, determining that the sensors of the vehicle are not calibrated properly based on the monitoring, generating a calibration target of an object on the road based on the sensor data, and adjusting a calibration parameter of the one or more sensors of the vehicle based on the generated calibration target.

A horizontal correction method for a detection platform implemented in an electronic device includes controlling a laser device to emit laser to a plurality of points on a motion platform and calculates a height value of each of the plurality of points, calculating tilt data of the motion platform according to the height value of each of the plurality of points; determining position compensation data of the motion platform according to the tilt data; and controlling the motion platform to move according to the position compensation data, and adjusting a position of the motion platform to a horizontal position.

The present application provides a position detecting method, device and storage medium for a vehicle ladar, where the method includes: detecting, through a ladar disposed on an autonomous vehicle, detection data of at least one wall of an interior room in which the autonomous vehicle is located, obtaining a point cloud image according to the detection data of the at least one wall, and judging, according to the point cloud image, whether an installation position of the ladar is accurate. According to the technical solution, it is possible to accurately detect whether the installation position of the ladar is accurate, provide a prerequisite for calibration of the installation position of the ladar, and improve detection accuracy of the ladar for obstacles around the autonomous vehicle.

A laser scanner and a system with a laser scanner for measuring an environment. The laser scanner includes an optical distance measuring device, a support, a beam steering unit rotatably fixed to the support which rotates around a beam axis of rotation. The beam steering unit includes a mirrored surface which deflects radiation used in the optical distance measurement and an angle encoder for recording angle data. The optical distance measurement is performed by a progressive rotation of the beam steering unit about the beam axis of rotation and the continuous emission of a distance measurement radiation, the emission being made through an outlet area arranged in the direction of the mirrored surface on the support, the receiving optics for receiving radiation are arranged on the support, and wherein the outlet area has a lateral offset with respect to the optical axis of the receiving optics.

Provided is an optical device capable of suppressing variations in the range for scanning light. This optical device comprises: a light source that emits a laser beam; a MEMS mirror that scans the laser beam toward a predetermined range; and a diffraction grating that guides the laser beam to the MEMS mirror by guiding the laser beam in a direction corresponding to the wavelength thereof. The optical device also comprises an MEMS control unit that performs control such that, by employing a change in the optical path of the laser beam caused through the diffraction grating by a change in the wavelength of the laser beam, variations in the scanning range of the laser beam by the MEMS mirror are suppressed.

Described herein are various embodiments for identifying miscalibrations in LiDAR sensors installed on an ADV in real time while the ADV is in motion, and notifying a user that the LiDAR sensors needs to be recalibrated. An exemplary method includes calculating an initial number of overlapping cloud points between the cloud point data from a first LiDAR sensor and a second LiDAR sensor; and replacing a set of existing calibration parameters of the second LiDAR sensor with multiple sets of recalibration parameters to calculate multiple revised numbers of overlapping cloud points between the point cloud data. A potential miscalibration can be detected in the first LiDAR sensor or the second LiDAR sensor when the initial number of overlapping cloud points is smaller than at least one revised number of overlapping cloud points. The potential miscalibration can be verified by repeating the above operations multiple times with a time of time following each repetition.