Sensor network perception for mobile robotics

Abstract

The dominant architecture for mobile robot perception uses sensors on-board the robot, providing only a first-person perspective on the environment. This work describes a novel mobile robot system that uses an environment-based sensor network, providing a powerful third-person perspective on the environment. In our previous work (1999), we described an algorithm that computes a real-time spatial-temporal occupancy map from the multiple video streams of the sensor network. We also described a novel path-planning algorithm based upon this system. In this work we describe a novel motion control loop that is based upon tracking the mobile robot in the occupancy map. Tracking in the fused perceptual space of the sensor network provides several advantages over tracking individually in a set of raw sensor spaces. We demonstrate a prototype system operating in several dynamic scenarios.