Receding horizon path planning for 3D exploration and surface inspection

  • Andreas Bircher
  • Mina Kamel
  • Kostas Alexis
  • Helen Oleynikova
  • Roland Siegwart

DOI: 10.1007/s10514-016-9610-0

Cite this article as:
Bircher, A., Kamel, M., Alexis, K. et al. Auton Robot (2016). doi:10.1007/s10514-016-9610-0
Part of the following topical collections:
  1. Active Perception


Within this paper a new path planning algorithm for autonomous robotic exploration and inspection is presented. The proposed method plans online in a receding horizon fashion by sampling possible future configurations in a geometric random tree. The choice of the objective function enables the planning for either the exploration of unknown volume or inspection of a given surface manifold in both known and unknown volume. Application to rotorcraft Micro Aerial Vehicles is presented, although planning for other types of robotic platforms is possible, even in the absence of a boundary value solver and subject to nonholonomic constraints. Furthermore, the method allows the integration of a wide variety of sensor models. The presented analysis of computational complexity and thorough simulations-based evaluation indicate good scaling properties with respect to the scenario complexity. Feasibility and practical applicability are demonstrated in real-life experimental test cases with full on-board computation.


Exploration planning Next-best-view Autonomous inspection Aerial robotics 

Funding information

Funder NameGrant NumberFunding Note
European Union’s Horizon 2020 Research and Innovation Programme
  • No.644128
University of Nevada, Reno seed funds

    Copyright information

    © Springer Science+Business Media New York 2016

    Authors and Affiliations

    1. 1.ETH ZurichZurichSwitzerland
    2. 2.University of Nevada, RenoRenoUSA

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