Estimating Object Shape and Movement Using Local Occupancy Grid Maps⁎. Issue 8 (2019) - Quehl, Jannik; Yan, Shengchao; Wirges, Sascha; Pauls, Jan-Hendrik; Lauer, Martin
Abstract: Estimating motion and shape of surrounding objects reliably and accurately is a fundamental challenge in the study of interactions between cooperative traffic participants. This paper proposes a new approach that utilizes free space information obtained from a LiDAR sensor and object local grid maps in order to simultaneously estimate the shape and movement state of objects with arbitrary shape. We evaluated our approach in several simulated scenarios and found that the movement and shape estimation results are very close to the ground truth. Finally, we did a qualitative evaluation on real data extracted from the KITTI benchmark.