Autonomous Room Acoustic Measurements using Rapidly-Exploring Random Trees and Gaussian Processes

Georg Götz, Ishwarya Ananthabhotla, Sebastià V. Amengual Garí, Paul T. Calamia

Research output: Contribution to conferencePaperScientificpeer-review

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Various robot systems have been proposed in the past to automate the tedious and time-consuming room acoustic measurement process. While small-scale measurements within a limited area can be realized with robotic arms, room-scale measurements require robots that can travel larger distances and ideally navigate through their environment autonomously. In this paper, we propose a new measurement strategy for large-scale, autonomous, room-acoustic measurement robots. The measurement strategy uses rapidly-exploring random trees to determine multiple candidate paths, from which it chooses the best path for exploring the unvisited parts of the environment and reconstructing a target acoustic metric. Gaussian process regression is used to incrementally merge new acoustic data into a global estimate. We evaluate the measurement strategy in a multi-room scenario, utilizing a late reverberation metric and a robot system consisting of a source and a receiver robot. We demonstrate that the measurement strategy can be used to map and reconstruct late reverberation characteristics over a large area.
Original languageEnglish
Number of pages8
Publication statusAccepted/In press - 2023
MoE publication typeNot Eligible
EventForum Acusticum - Torino, Italy, Torino, Italy
Duration: 10 Sept 202315 Sept 2023


ConferenceForum Acusticum


  • room acoustic measurements
  • measurement robot
  • path planning
  • late reverberation


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