3D Localization of Multiple Moving People by a Omnidirectional Stereo System of Cooperative Mobile Robots

摘要

Flexible, reconfigurable vision systems can provide an extremely rich sensing modality for sophisticated multiple robot platforms. We propose a cooperative and adaptive approach of panoramic vision to the problem of finding and protecting humans by a robot team in an emergency circumstance (e.g. a rescue in an office building). A panoramic virtual stereo vision method is proposed for this cooperative approach, which features omni-directional visual sensors, cooperative mobile platforms, selected 3D matching, and real-time moving object (people) detection and tracking. The problems of dynamic self-calibration of moving platforms, robust 3D localization of moving human subjects, and cooperative strategies between two robots are discussed. We have found that the localization errors of a human target by the panoramic virtual stereo is subject to three different kinds of errors: the calibration error of the panoramic virtual stereo, matching error of widely separated views, and triangulation error of the panoramic stereo pair. A careful numerical analysis of the error characteristics of the panoramic virtual stereo is presented in order to derive rules for optimal view planning of moving sensing platforms (mobile robots) or multiple (more than two) stationary sensing platforms. Experimental results are given for detecting and localizing multiple moving objects using two cooperative robot platforms. 1 I.