Paper Info
Title
An incremental sampling-based approach to inspection planning: the rapidly exploring random tree of trees.
Abstract
A new algorithm, called rapidly exploring random tree of trees (RRTOT) is proposed, that aims to address the challenge of planning for autonomous structural inspection. Given a representation of a structure, a visibility model of an onboard sensor, an initial robot configuration and constraints, RRTOT computes inspection paths that provide full coverage. Sampling based techniques and a meta-tree structure consisting of multiple RRT* trees are employed to find admissible paths with decreasing cost. Using this approach, RRTOT does not suffer from the limitations of strategies that separate the inspection path planning problem into that of finding the minimum set of observation points and only afterwards compute the best possible path among them. Analysis is provided on the capability of RRTOT to find admissible solutions that, in the limit case, approach the optimal one. The algorithm is evaluated in both simulation and experimental studies. An unmanned rotorcraft equipped with a vision sensor was utilized as the experimental platform and validation of the achieved inspection properties was performed using 3D reconstruction techniques.
Year
DOI
Venue
2017
10.1017/S0263574716000084
ROBOTICA
Keywords
Field
DocType
Inspection path planning,Coverage path planning,Aerial robotics,Unmanned aerial vehicles
Computer vision,Rapidly exploring random tree,Control engineering,Artificial intelligence,Sampling (statistics),Engineering,Machine learning
Journal
Volume
Issue
ISSN
35
6
0263-5747
Citations 
PageRank 
References 
7
0.52
8
Authors
6
Name
Order
Citations
PageRank
andreas bircher1341.74
Kostas Alexis2544.00
Ulrich Schwesinger3333.16
sammy omari42218.70
M. Burri534318.62
Roland Siegwart67640551.49