Detecting Moving Objects using a Single Camera on a Mobile Robot in an Outdoor Environment

Abstract

Robust detection of moving objects from a mobile robot is required for safe outdoor navigation, but is not easily achievable since there are two motions involved: the motions of moving objects and the motion of the sensors used to detect the objects. We have experimented with a probabilistic approach for moving object detection from a mobile robot using a single camera in outdoor environments. The ego-motion of the camera is compensated using corresponding feature sets and outlier detection, and the positions of moving objects are estimated using an adaptive particle lter and EM al- gorithm. The algorithms are implemented and tested on three different robot platforms (robotic helicopter, Segway RMP, and Pioneer2 AT) in an outdoor environment, and the detection results are analyzed.