Localizing victims through sound and probabilistic grid maps in an urban search and rescue scenario

Abstract

Sound source localization can be used in the Robocup Rescue Robots League as a sensor that is capable to autonomously detect victims that emit sound. Using differential time of flight measurements through energy cross-spectrum evaluation of the sound signals, the angular direction to multiple sound sources can be determined with a pair of microphones for SNRs better than -8dB. Assuming that the robot pose is known, this information is sufficient to create probabilistic occupancy grid map of the sound sources in the environment and thus localize the victims in a global map. This has been demonstrated using example measurements in an urban search and rescue scenario. © Springer-Verlag Berlin Heidelberg 2006.