Cooperative People Tracking Using Multiple Ground Lidars Based on Distributed Interacting Multimodel Estimator
Takuji Nakahira, Masafumi Hashimoto, K. Takahashi · 2019
This paper presents a cooperative people tracking using two networked lidars allocated in an environment as sensor nodes. The tilt angles, heights, and relative poses of the two lidars are calibrated based on the lidar-scan data for accurate tracking. After the position data of people are extracted from the lidar-scan data using a background subtraction method, poses and behaviors of people, such as stopping, walking, and suddenly rushing out, are estimated based on a distributed interacting-multimodel (DIMM) estimator. The DIMM-based tracker works in any sensor network topologies, and therefore, this may provide a degree of scalability and robustness that cannot be achieved by conventional centralized interacting-multimodel (CIMM) based tracker with a central server. Experimental results reveal the tracking performance of the proposed DIMM-based tracker by comparison with the CIMM-based tracker.