This paper presents a two-step framework for creating the three-dimensional (3-D) sound map of an environment with a mobile robot. The first step is the creation of a map that describes the geometry of the environment. The second step is the addition of the acoustic information to the geometric map. The result is a sound map that shows the probability of emitting sound for all the structures in the environment. To build the sound map, a mobile robot equipped with a microphone array drives through the mapped environment. During this drive, the acoustic information gathered by the microphone array is accumulated in a probabilistic manner. First, the likelihood of sound source presence in a set of directions is evaluated from the acoustic power received from these directions. Then, using an estimate of the robot's pose, an acoustic ray casting procedure transfers this likelihood to the structures in the geometric map. Finally, the probability that these structures emit sound is updated accordingly to the likelihood. Experimental results show that the sound maps are: accurate as it was possible to localize sound sources in 3-D and practical as different types of environments were mapped.

This paper presents a framework for creating a 3D map of an environment that contains the probability of a geometric feature to emit a sound. The goal is to provide an automated tool for condition monitoring of plants. The map is created by a mobile platform equipped with a microphone array and laser range sensors. The microphone array is used to estimate the sound power received from different directions whereas the laser range sensors are used for estimating the platform pose in the environment. During navigation, a ray casting method projects the audio measurements made onboard the mobile platform to the map of the environment. Experimental results show that the created map is an efficient tool for sound source localization.