Vision-based cooperative simultaneous localization and tracking

Abstract

Localization is one of the most essential capabilities of autonomous robots. Cooperative localization has been proved to be effective in multi-robot localization. However, nearby moving objects could degrade the cooperative localization performance. In this paper, we demonstrate that the cooperative simultaneous localization and tracking approach is superior in challenging scenarios. Localization and moving object tracking are mutually beneficial. The proposed approach is evaluated using humanoid robots in the RoboCup environment in which only uncertain data from onboard cameras and odometry are used. Ample experimental results with ground truthing from laser scanners demonstrate the accuracy and feasibility of the proposed vision-based cooperative simultaneous localization and tracking algorithm.