%0 Conference Paper %1 IAV2013 %A Zhang, Liang %A Li, Qingquan %A Li, Ming %A Mao, Q.Zh %A Nüchter, A. %B Proceedings of the 6th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '13) %C Gold Coast, Australia %D 2013 %K imported %N 1 %R 10.3182/20130626-3-AU-2035.00058 %T Multiple Vehicle-like Target Tracking Based on Velodyne Lidar %U https://robotik.informatik.uni-wuerzburg.de/telematics/download/iav2013.pdf %V 8 %X This paper proposes a novel multiple vehicle-like target tracking method based on a Velodyne HDL64E light detection and ranging (LiDAR) system. The proposed method combines multiple hypothesis tracking (MHT) algorithm with dynamic point cloud registration (DPCR), which is able to solve the multiple vehicle-like target tracking in highly dynamic urban environments without any auxiliary information from GPS or IMU. Specifically, to track targets consistently, the DPCR is developed to calculate accurately the pose of the ego-vehicle for the transformation of raw measurements taken in the moving coordinate systems into a static absolute coordinate system; while in turn, MHT helps to improve the performance of DPCR by discriminating and removing the dynamic points from the scene. Furthermore, the proposed MHT method is also able to solve the occlusion problem existing in the point cloud. Experiments on sets of urban environments prove that the presented method is effective and robust, even in highly dynamic environments.

@inproceedings{IAV2013, abstract = {This paper proposes a novel multiple vehicle-like target tracking method based on a Velodyne HDL64E light detection and ranging (LiDAR) system. The proposed method combines multiple hypothesis tracking (MHT) algorithm with dynamic point cloud registration (DPCR), which is able to solve the multiple vehicle-like target tracking in highly dynamic urban environments without any auxiliary information from GPS or IMU. Specifically, to track targets consistently, the DPCR is developed to calculate accurately the pose of the ego-vehicle for the transformation of raw measurements taken in the moving coordinate systems into a static absolute coordinate system; while in turn, MHT helps to improve the performance of DPCR by discriminating and removing the dynamic points from the scene. Furthermore, the proposed MHT method is also able to solve the occlusion problem existing in the point cloud. Experiments on sets of urban environments prove that the presented method is effective and robust, even in highly dynamic environments.}, added-at = {2017-09-19T13:40:53.000+0200}, address = {Gold Coast, Australia}, author = {Zhang, Liang and Li, Qingquan and Li, Ming and Mao, Q.Zh and N{\"u}chter, A.}, biburl = {https://www.bibsonomy.org/bibtex/2ca2354c868d179b7a29d87c9e318e486/nuechter76}, booktitle = {Proceedings of the 6th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '13)}, doi = {10.3182/20130626-3-AU-2035.00058}, interhash = {69b55784b7ac2336d5a0512ce26df3e6}, intrahash = {ca2354c868d179b7a29d87c9e318e486}, keywords = {imported}, month = {June}, number = 1, timestamp = {2017-09-29T16:01:21.000+0200}, title = {{Multiple Vehicle-like Target Tracking Based on Velodyne Lidar}}, url = {https://robotik.informatik.uni-wuerzburg.de/telematics/download/iav2013.pdf}, volume = 8, year = 2013 }