Chowdhury, AR (2022) Learning to Listen and Move: An Implementation of Audio-Aware Mobile Robot Navigation in Complex Indoor Environment. In: 39th IEEE International Conference on Robotics and Automation, ICRA 2022, 23 - 27 May 2022, Philadelphia, pp. 3699-3705.
PDF
39th IEEE- ICRA 2022_3699-3705_2022.pdf - Published Version Restricted to Registered users only Download (4MB) | Request a copy |
Abstract
Sound is an essential navigation cue that intelligent robots can leverage for localizing sound-emitting targets. This work introduces a framework for the audio-aware navigation task of mobile robots equipped with a microphone array in a complex indoor environment. The robot initialized at a random starting position has to accurately localize a distant sound source and plan an optimal path towards the sound-emitting target. Auto-encoders are used to extract implicit acoustic features that are robust against environmental noise and reverberation. The proposed framework is based on two key ideas - a sound inference module (SIM) that maps the perceived acoustic information to a given geometric map of the physical space, and a path planner that generates a path from the robot's current position to the estimated position of the sound source. Experimental results show that the SIM achieved a minimum and maximum localization error of 0.31 m and 0.70 m at a robot-source distance of 1 m and 6 m, respectively at different environmental configurations. Additionally, the proposed framework achieved a minimum and maximum reliability of 4.38 m-1 and 2.31 m-1 at a robot-source distance of 1 m and 6 m, respectively under the influence of background noise.
Item Type: | Conference Paper |
---|---|
Publication: | Proceedings - IEEE International Conference on Robotics and Automation |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc. |
Keywords: | Acoustic generators; Audio acoustics; Complex networks; Convolutional neural networks; Indoor positioning systems; Intelligent robots; Microphone array; Mobile robots; Navigation; Robot programming, Audio-aware navigation; Auto encoders; Convolutional neural network; Indoor environment; Mobile Robot Navigation; Navigation tasks; Sound source; Sound source localization, Motion planning |
Department/Centre: | Division of Mechanical Sciences > Centre for Product Design & Manufacturing |
Date Deposited: | 15 Sep 2022 05:06 |
Last Modified: | 15 Sep 2022 05:06 |
URI: | https://eprints.iisc.ac.in/id/eprint/76463 |
Actions (login required)
View Item |