Stereo Vision-based Localization for Hexapod Walking Robots Operating in Rough Terrains

THOMAS FISCHER; TAIHÚ PIRE; PETR ČÍ?EK; PABLO DE CRISTÓFORIS; JAN FAIGL

Daejeon

Conferencia; 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 2016

Institute of Electrical and Electronics Engineers (IEEE)

This paper concerns the problem of self-localisation for a hexapod walking robot moving in rough terrains. Given that legged robots exhibit higher terrain pass-ability than wheeled or tracked platforms when operating in harsh environments, they constitute a challenge for the localization techniques because the camera motion between consecutive frames can be arbitrary due to the motion gait and terrain irregularities. In this paper we present and evaluate an inertially assisted stereo parallel tracking and mapping (S- PTAM) method deployed on a hexapod crawling robot operating in rough terrain. The deployment scenario is motivated by autonomous navigation in an unknown environment in an open loop fashion. The reported results and comparison with an existing RGB-D SLAM technique show the feasibility of the proposed approach.