Effect of fast motion on range images acquired by lidar scanners for automotive applications

The scanning process of lidar scanners is extended over time. Hence, relative motion between sensor and object during the scanning leads to a motion-dependent blur, here called motion-scan effect. Due to this effect the lidar's distance map is deteriorated, which has a negative impact on the subsequent signal processing. This paper quantifies this effect and compares it to statistical errors. In order to compensate for the negative impact, motion models for a simple car model are formulated, and the model parameters are checked for identifiability. Identification of the parameters allows to compensate for the effect. Thus the accuracy and the control mode can be improved, which is particularly important for. safety-critical applications, e.g., autonomous vehicles.