Autonomous Robots

, Volume 40, Issue 6, pp 1059–1078 | Cite as

Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots

  • Andreas Bircher
  • Mina Kamel
  • Kostas AlexisEmail author
  • Michael Burri
  • Philipp Oettershagen
  • Sammy Omari
  • Thomas Mantel
  • Roland Siegwart


This paper presents a new algorithm for three-dimensional coverage path planning for autonomous structural inspection operations using aerial robots. The proposed approach is capable of computing short inspection paths via an alternating two-step optimization algorithm according to which at every iteration it attempts to find a new and improved set of viewpoints that together provide full coverage with decreased path cost. The algorithm supports the integration of multiple sensors with different fields of view, the limitations of which are respected. Both fixed-wing as well as rotorcraft aerial robot configurations are supported and their motion constraints are respected at all optimization steps, while the algorithm operates on both mesh- and occupancy map-based representations of the environment. To thoroughly evaluate this new path planning strategy, a set of large-scale simulation scenarios was considered, followed by multiple real-life experimental test-cases using both vehicle configurations.


Coverage planning Aerial robots Autonomous inspection 



This work has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Grant Agreement No.644128, AEROWORKS.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Andreas Bircher
    • 1
  • Mina Kamel
    • 1
  • Kostas Alexis
    • 1
    • 2
    Email author
  • Michael Burri
    • 1
  • Philipp Oettershagen
    • 1
  • Sammy Omari
    • 1
  • Thomas Mantel
    • 1
  • Roland Siegwart
    • 1
  1. 1.ETH ZurichZurichSwitzerland
  2. 2.University of NevadaRenoUSA

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