Skip to Main content Skip to Navigation
Conference papers

Long-term robot motion planning for active sound source localization with Monte Carlo tree search

Quan V. Nguyen 1 Francis Colas 1 Emmanuel Vincent 2 François Charpillet 1
1 LARSEN - Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
2 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : We consider the problem of controlling a mobile robot in order to localize a sound source. A microphone array can provide the robot with information on source localization. By combining this information with the movements of the robot, the localization accuracy can be improved. However, random robot motion or short-term planning may not result in optimal localization. In this paper, we propose an optimal long-term robot motion planning algorithm for active source lo-calization. We introduce a Monte Carlo tree search (MCTS) method to find a sequence of robot actions that minimize the entropy of the belief on the source location. A tree of possible robot movements which balances between exploration and exploitation is first constructed. Then, the movement that leads to minimum uncertainty is selected and executed. Experiments and statistical results show the effectiveness of our proposed method on improving sound source localization in the long term compared to other motion planning methods.
Document type :
Conference papers
Complete list of metadatas
Contributor : Quan Nguyen <>
Submitted on : Friday, January 27, 2017 - 11:30:09 AM
Last modification on : Monday, May 4, 2020 - 11:37:58 AM
Document(s) archivé(s) le : Friday, April 28, 2017 - 5:35:47 PM


Files produced by the author(s)


  • HAL Id : hal-01447787, version 1


Quan V. Nguyen, Francis Colas, Emmanuel Vincent, François Charpillet. Long-term robot motion planning for active sound source localization with Monte Carlo tree search. HSCMA 2017 - Hands-free Speech Communication and Microphone Arrays , Mar 2017, San Francisco, United States. ⟨hal-01447787⟩



Record views


Files downloads