Predictive Mover Detection and Tracking in Cluttered Environments
journal contributionposted on 01.01.2006 by Luis Navarro-Serment, Christoph Mertz, Martial Hebert
Any type of content formally published in an academic journal, usually following a peer-review process.
This paper describes the design and experimental evaluation of a system that enables a vehicle to detect and track moving objects in real-time. The approach investigated in this work detects objects in LADAR scan lines and tracks these objects (people or vehicles) over time. The system can fuse data from multiple scanners for 360° coverage. The resulting tracks are then used to predict the most likely future trajectories of the detected objects. The predictions are intended to be used by a planner for dynamic object avoidance. The perceptual capabilities of our system form the basis for safe and robust navigation in robotic vehicles, necessary to safeguard soldiers and civilians operating in the vicinity of the robot.