Group Multi-Object Tracking for Dynamic Risk Map and Safe Path Planning
Lyuyu Shen, Hongliang Guo, Yechao Bai, Lei Hua Qin, Marcelo H. Ang, Daniela L. Rus · 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · 2021
This paper studies the group multi-object tracking (MOT) problem in dynamic pedestrian environments, with intended application to safe navigation for autonomous vehicles. We complete a full autonomous vehicle navigation pipeline from object detection, tracking, grouping, to risk map generation and safe path planning. Our main contribution is to instantiate a group multi-object tracking algorithm, which provides the crucial grouped activity information, i.e. group position, group velocity, group size, to the risk map generator, and therewith produce a stable and robust risk map for the downstream safe path planner. Experimental results with real world data show the socially acceptable, robust and stable performance of the proposed algorithm over its individual MOT counterpart.