TY - GEN
T1 - Normal Distribution Mixture Matching based Model Free Object Tracking Using 2D LIDAR
AU - Choi, Baehoon
AU - Jo, Hyung Gi
AU - Kim, Euntai
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85081166080
U2 - 10.1109/IROS40897.2019.8967876
DO - 10.1109/IROS40897.2019.8967876
M3 - Conference paper
AN - SCOPUS:85081166080
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 455
EP - 461
BT - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
Y2 - 3 November 2019 through 8 November 2019
ER -