HESAI TECHNOLOGY CO., LTD.

A method for evaluating degree of an interstitial point of point cloud includes: building a tester, including a base, a first object, and a second object; mounting a LiDAR on the base, to cause that light emitted by the LiDAR can be incident to the first object and the second object; emitting detection pulses to the first object and the second object by the LiDAR; receiving echo pulses reflected by the first object and the second object, and generating point cloud based on the echo pulses; determining whether an interstitial point exists in the point cloud; increasing the distance between the first object and the second object when an interstitial point exists in the point cloud; repeating until no interstitial point exists in the point cloud, and recording the distance between the first object and the second object at this moment, to characterize the degree of the interstitial point.

A signal transmitting and receiving system and a method thereof are provided in this disclosure. The system includes: a transmitter circuit configured to generate a trigger signal at a trigger moment based on a first clock signal and transmit a detection signal at a transmitting time point; and a receiver circuit configured to receive an echo signal generated by reflection of the detection signal by a target object, and receive the trigger signal based on a second clock signal and enable a first receiving channel at an initial start time point, where the first receiving channel takes the initial start time point as a time origin and senses a return time point of receiving the echo signal: determining a first calculation start point of the first receiving channel, and determining a target time difference between the return time point sensed by the first receiving channel and the transmitting time point based on the first calculation start point, where a first delay of the initial start time point relative to the trigger time point includes an unpredictable jitter delay. Based on the signal transmitting and receiving system and the method thereof of this disclosure, a problem of a jitter of a scanning start point when a receiving system and a transmitting system are clocked asynchronously can be solved, and it is possible to accumulate scanning data in multiple scans in a chip, thereby further increasing a signal-to-noise ratio and improving a ranging capability and application scenarios of a receiving chip.

This disclosure provides a diagnostic method for a position and orientation of a LiDAR, where the LiDAR is fixed to an apparatus, the diagnostic method including: determining a first reference data of scanning a calibration object by the LiDAR when it is in a standard position and orientation; controlling the LiDAR to scan the calibration object in a current position and orientation and collect a first measurement data of the LiDAR; and determining, based on the first reference data and the first measurement data, whether the current position and orientation of the LiDAR deviates from the standard position and orientation. In embodiments of this disclosure, using the characteristics of point cloud data of the LiDAR, the LiDAR diagnoses by itself an abnormal change in its relative position and orientation to the apparatus during the normal operation without the cooperation of other detector devices. Calculations of the diagnostic method are simple, and results are accurate. Embodiments of this disclosure further provide a LiDAR and an autonomous driving vehicle. By using the aforementioned diagnostic method, the relative position and orientation of the LiDAR to the autonomous driving vehicle can be quickly and accurately diagnosed, which can ensure safe operation of the autonomous driving vehicle.

A calibration method, a calibration device (M 10 ), a calibration system, and a readable storage medium. the calibration method comprises: receiving a point cloud determined by a LiDAR (LS 1 ) from a field of view, the point cloud being in a LiDAR coordinate system (S 11 ); receiving a set of survey points determined from the field of view by a survey device (CH 1 ), the set of survey points being in a survey coordinate system (S 12 ); based on the point cloud and the set of survey points, determining a first transformation parameter between the LiDAR coordinate system and the survey coordinate system (S 13 ); based on the first transformation parameter and the position and orientation information of the vehicle (CA 1 ) in the survey coordinate system (S 14 ), determining a calibration parameter (S 14 ) between the LiDAR coordinate system and the vehicle coordinate system of the vehicle (CA 1 ). Both the calibration efficiency and the calibration precision can be improved, and batch calibration is facilitated.