Probabilistic approach for building auditory maps with a mobile microphone array

This paper presents a multi-modal sensor approach for mapping sound sources using an omni-directional microphone array on an autonomous mobile robot. A fusion of audio data (from the microphone array), odometry information and the laser range scan data (from the robot) was used to precisely localize and map the audio sources in an environment. An audio map is created while the robot is autonomously navigating through the environment by continuously generating audio scans with a steered response power (SRP) algorithm. Using the poses of the robot, rays are cast in the map in all directions given by the SRP. Then each occupied cell in the geometric map hit by a ray is assigned a likelihood of containing a sound source. This likelihood is derived from the SRP at that particular instant. Since the localization of the robot is probabilistic, the uncertainty in the pose of the robot in the geometric map is propagated to the occupied cells hit during the ray casting. This process is repeated while the robot is in motion and the map is updated after every audio scan. The generated sound maps were reused and the changes in the audio environment were updated by the robot as it identifies these changes.