Receding horizon path planning for 3D exploration and surface inspection

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 plann...

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Bibliographic Details
Published in:Autonomous robots Vol. 42; no. 2; pp. 291 - 306
Main Authors: Bircher, Andreas, Kamel, Mina, Alexis, Kostas, Oleynikova, Helen, Siegwart, Roland
Format: Journal Article
Language:English
Published: New York Springer US 01.02.2018
Springer Nature B.V
Subjects:
Active Perception
Algorithms
Artificial Intelligence
Complexity
Computer Imaging
Computer simulation
Control
Engineering
Exploration
Horizon
Inspection
Mechatronics
Micro air vehicles (MAV)
Path planning
Pattern Recognition and Graphics
Planning
Robotics
Robotics and Automation
Rotary wing aircraft
Vision
Next-best-view
Autonomous inspection
Aerial robotics
Exploration planning
ISSN:0929-5593, 1573-7527
Online Access:Get full text
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Summary: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.
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ISSN:0929-5593
1573-7527
DOI:10.1007/s10514-016-9610-0