Stereo Vision-based Autonomous Target Detection and Tracking on an Omnidirectional Mobile Robot

Abstract

In this paper, a mobile robot equipped with an onboard computing unit and a stereo camera for autonomous target detection and tracking is introduced. This system can figure out an interesting target and track it robustly in real time. It is based on the ROS framework and can handle multi-resource information, such as RGB images, depth information, and IMU data. To balance the performance of the machine learning based object detection algorithm and the algorithm for object tracking, the Hamming distance and the intersection over union are selected as criteria. The performance of the system is verified in a hardware experiment in two typical scenarios.