Person Following of a Mobile Robot using Stereo Vision

Abstract

This paper describes a stereo-based person detection and tracking method for a mobile robot that can follow a specific person in dynamic environments. Many previous works on person detection use laser range finders which can provide very accurate range measurements. Stereo-based systems have also been popular, but most of them have not been used for controlling a real robot. We propose a detection method using depth templates of person shape applied to a dense depth image. We also develop an SVM-based verifier for eliminating false positive. For person tracking by a mobile platform, we formulate the tracking problem using the Extended Kalman filter. The robot continuously estimates the position and the velocity of persons in the robot local coordinates, which are then used for appropriately controlling the robot motion. Although our approach is relatively simple, our robot can robustly follow a specific person while recognizing the target and other persons with occasional occlusions.