In this paper, a novel normal distribution mixture matching based model free object tracking algorithm using 2D LIDAR is proposed. Each target object is modeled as a normal distribution mixture that captures the distribution of the points scanned from the surface of the object. This novel representation enables normal distribution transform (NDT) to accurately estimate the motion of objects, even if the shape of the points differs depending on where it is observed. Our evaluation of the proposed algorithm shows good performance in practical applications. In addition, we provides an alternative way of segmentation and data association using occupancy grid map to avoid a problem that defines a distance metric between the mixture and the point cloud. As a result, the proposed algorithm works in real time in our experiments.
|Title of host publication||2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||7|
|Publication status||Published - 2019 Nov|
|Event||2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China|
Duration: 2019 Nov 3 → 2019 Nov 8
|Name||IEEE International Conference on Intelligent Robots and Systems|
|Conference||2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019|
|Period||19/11/3 → 19/11/8|
Bibliographical noteFunding Information:
This work was supported in part by LG Electronics, Development of multiple object tracking (MOT) algorithm in dynamic environment. This work was also supported in part by the Industry Core Technology Development Project, 20005062, Development of Artificial Intelligence Robot Autonomous Navigation Technology for Agile Movement in Crowded Space, funded by the Ministry of Trade, industry & Energy (MOTIE, Republic of Korea).
© 2019 IEEE.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Vision and Pattern Recognition
- Computer Science Applications