AIMASDASOct 9, 2023

Measuring Acoustics with Collaborative Multiple Agents

Tsinghua
arXiv:2310.05368v116 citationsh-index: 20
Originality Incremental advance
AI Analysis

This addresses the inefficiency of traditional RIR measurement methods for applications in acoustics and robotics, though it appears incremental as it builds on existing multi-agent and acoustic concepts.

The paper tackles the problem of measuring environment acoustics, specifically Room Impulse Responses (RIRs), by proposing a method using two robots that actively move and emit/receive signals, trained with a collaborative multi-agent policy to explore acoustics and minimize prediction error.

As humans, we hear sound every second of our life. The sound we hear is often affected by the acoustics of the environment surrounding us. For example, a spacious hall leads to more reverberation. Room Impulse Responses (RIR) are commonly used to characterize environment acoustics as a function of the scene geometry, materials, and source/receiver locations. Traditionally, RIRs are measured by setting up a loudspeaker and microphone in the environment for all source/receiver locations, which is time-consuming and inefficient. We propose to let two robots measure the environment's acoustics by actively moving and emitting/receiving sweep signals. We also devise a collaborative multi-agent policy where these two robots are trained to explore the environment's acoustics while being rewarded for wide exploration and accurate prediction. We show that the robots learn to collaborate and move to explore environment acoustics while minimizing the prediction error. To the best of our knowledge, we present the very first problem formulation and solution to the task of collaborative environment acoustics measurements with multiple agents.

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