Robust sound source mapping using three layered selective audio rays for mobile robots
This paper investigates sound source mapping in a real environment using a mobile robot. Our approach is based on audio ray tracing which integrates occupancy grids and sound source localization using a laser range finder and a microphone array. Previous audio ray tracing approaches rely on all observed rays and grids. As such observation errors caused by sound reflection, sound occlusion, wall occlusion, sounds at misdetected grids, etc. can significantly degrade the ability to locate sound sources in a map. A three layered selective audio ray tracing mechanism is proposed in this work. The first layer conducts frame based unreliable ray rejection (sensory rejection) considering sound reflection and wall occlusion. The second layer introduces triangulation and audio tracing to detect falsely detected sound sources, rejecting audio rays associated to these misdetected sounds sources (short term rejection) A third layer is tasked with rejecting rays using the whole history (long term rejection) to disambiguate sound occlusion. Experimental results under various situations are presented, which proves the effectiveness of our method.
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)