Audio-based Relative Positioning System for Multiple Micro Air Vehicle Systems

Employing a group of independently controlled flying micro air vehicles (MAVs) for aerial coverage missions, instead of a single flying robot, increases the robustness and efficiency of the missions. Designing a group of MAVs requires addressing new challenges, such as inter-robot collision avoidance and formation control, where individual's knowledge about the relative location of their local group members is essential. A relative positioning system for a MAV needs to satisfy severe constraints in terms of size, weight, processing power, power consumption, three-dimensional coverage and price. In this paper we present an on-board audio based system that is capable of providing individuals with relative positioning information of their neighbouring sound emitting MAVs. We propose a method based on coherence testing among signals of a small onboard microphone array to obtain relative bearing measurements, and a particle filter estimator to fuse these measurements with information about the motion of robots throughout time to obtain the desired relative location estimates. A method based on fractional Fourier transform (FrFT) is used to identify and extract sounds of simultaneous chirping robots in the neighbourhood. Furthermore, we evaluate our proposed method in a real world experiment with three simultaneously flying micro air vehicles.

Presented at:
Robotics: Science and Systems RSS2013, Berlin, Germany, June 24-28, 2013

 Record created 2013-12-10, last modified 2019-12-05

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