Audio-based Swarming MAVs

Project Overview

Robots within an aerial swarm need to localize themselves and to obtain the relative position of their neighbouring robots. In the case of small, lightweight and safe Micro Air Vehicle (MAV) swarms there are not many technologies that could provide individuals with such information. The most common approaches are based on GPS sensors. However, GPS vulnerability is considered to be one of the main problems that need to be solved before allowing MAVs to operate in civilian airspace. Inspired by the sense of hearing in some animal groups, we hypothesize that using sound could offer a promising solution.

In this project, we have so far shown the success of an audio-based system for:

  • Relative positioning:

      Audio based Relative Positioning System for Multiple Micro Air Vehicle Systems, RSS 2013

  •  Self-Localization:

     Audio based Localization system for swarms of Micro Air Vehicles, ICRA 2014 

We furthermore showed that such a system could also be exploited to locate acoustic targets on the ground, such as the sound of an emergency whistle in a search and rescue mission.         

  •  Acoustic Target Localization

     Robust Acoustic Source Localization of Emergency Signals from Micro Air Vehicles, IROS 2012



Behaviour-based emergency source localization system


Emergency sound source localization system for fixed wing MAVs

Design of emergency sound-source and audio-based micro air vehicles for search and rescue applications

Audio based leader following behaviour for multiple micro aerial vehicles


M. Basiri; F. Schill; P. Lima; D. Floreano : Localization of emergency acoustic sources by micro aerial vehicles; Journal of Field Robotics. 2017. DOI : 10.1002/rob.21733.
M. Basiri; F. S. Schill; P. Lima; D. Floreano : On-Board Relative Bearing Estimation for Teams of Drones Using Sound; IEEE Robotics and Automation Letters. 2016. DOI : 10.1109/LRA.2016.2527833.
M. Varga; M. Basiri; G. H. M. Heitz; D. Floreano : Distributed Formation Control of Fixed Wing Micro Aerial Vehicles for Uniform Area Coverage. 2015. IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany.
M. Basiri / D. Floreano; P. M. U. De Almeida Lima (Dir.) : Audio-based Positioning and Target Localization for Swarms of Micro Aerial Vehicles. Lausanne, EPFL, 2015. DOI : 10.5075/epfl-thesis-6508.
M. Basiri; F. S. Schill; D. Floreano; P. Lima : Audio-based Localization for Swarms of Micro Air Vehicles. 2014. IEEE International Conference on Robotics and Automation (ICRA 2014), Hong Kong, China, May 31 - June 7, 2014. p. 4729-4734. DOI : 10.1109/ICRA.2014.6907551.
M. Basiri; F. Schill; D. Floreano; P. Lima : Audio-based Relative Positioning System for Multiple Micro Air Vehicle Systems. 2013. Robotics: Science and Systems RSS2013, Berlin, Germany, June 24-28, 2013.
M. Basiri; F. S. Schill; P. Lima U.; D. Floreano : Robust Acoustic Source Localization of Emergency Signals from Micro Air Vehicles. 2012. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vilamoura, Algarve, Portugal, October 7-12, 2012.. p. 4737-4742.


Teams of flying robots are preferred over single robots because of their ability to accomplish aerial coverage tasks more robustly and more efficiently. Tasks such as security patrolling or searching for victims in a disaster area can benefit from several autonomous robots operating in parallel instead of a single robot. In addition, using multiple robots allows for the use of cheap, light and safe “Micro Air Vehicles” (MAVs) for complex tasks which would otherwise require a single large and expensive platform. Finally, multiple robots can accomplish tasks beyond the capabilities of a single robot. within an aerial swarm are required to interact with each other and to work together towards achieving a common goal. This introduces new problems such as collisions among robots and motion coordination. Drawing inspiration from natural swarms (e.g. flocking in birds and schooling in fishes), two key elements required for succesful motion coordination are:

  • Relative positioning (knowledge of the relative position of other swarm members)
  • Distributed control  (local control actions resulting in a global swarm behavior)

A relative positioning system for a MAV needs to satisfy severe constraints in terms of size, weight, processing power, power consumption and 3D coverage. This makes the current relative positioning technologies used in ground robots not applicable to MAVs.

In nature, hearing is a key sensory input which allows animals to communicate with each other and localize each other. Taking inspiration from nature and considering the success of acoustic sensors in satisfying the imposed constraints of the MAVs, we hypothesize that an audio-based relative positioning system could be promising in obtaining collision avoidance and coordinated motion in a swarm of MAVs. We propose an approach where each robot detects and localizes the sound of other robots via its onboard acoustic sensors and tries to use this information to perform local actions resulting in the desired swarm behaviours. One behaviour we aim to accomplish during this project is the “Hear-and-Avoid” behaviour for achieving collision-free navigation in a swarm of MAVs.