Tracking People from a Mobile Platform

Tracking people from a moving platform is a useful skill for the coming generation of service and human-interaction robots. It is also a challenging problem, involving sensing, interpretation, planning, and control, all in a real time and dynamic environment. Techniques used in existing people-trackers that operate from fixed locations, noting changes against a fixed background, are not applicable. Instead, we apply a vision-based approach using real-time stereo and 3D reconstruction, that explicitly models both foreground and background objects in an efficient manner. The main novelties of our approach include (1) remapping the stereo disparities to an orthographic “occupancy map”, which simplifies person modeling, and (2) updating a background occupancy map based on robot motion. The current version of our system, running on a Pioneer II mobile robot, can follow people at up to 1.2 m/s in an indoor environment.