Paper Info
Title
Physical Orienteering Problem For Unmanned Aerial Vehicle Data Collection Planning In Environments With Obstacles
Abstract
This letter concerns a variant of the orienteering problem (OP) that arises from multi-goal data collection scenarios where a robot with a limited travel budget is requested to visit given target locations in an environment with obstacles. We call the introduced OP variant the physical OP (POP). The POP sets out to determine a feasible, collision-free, path that maximizes collected reward from a subset of the target locations and does not exceed the given travel budget. The problem combines motion planning and combinatorial optimization to visit multiple target locations. The proposed solution to the POP is based on the variable neighborhood search (VNS) method combined with the asymptotically optimal sampling-based probabilistic road map (PRM*) method. The VNS-PRM*. uses initial low-dense roadmap that is continuously expanded during the VNS-based POP optimization to shorten paths of the promising solutions and, thus, allows maximizing the sum of the collected rewards. The computational results support the feasibility of the proposed approach by a fast determination of high-quality solutions. Moreover, an experimental verification demonstrates the applicability of the proposed VNS-PRM* approach for data collection planning for an unmanned aerial vehicle in an urban-like environment with obstacles.
Year
DOI
Venue
2019
10.1109/LRA.2019.2923949
IEEE ROBOTICS AND AUTOMATION LETTERS
Keywords
Field
DocType
Motion and Path Planning, Aerial Systems: Applications
Motion planning,Data collection,Mathematical optimization,Orienteering,Combinatorial optimization,Control engineering,Sampling (statistics),Engineering,Probabilistic logic,Robot,Asymptotically optimal algorithm
Journal
Volume
Issue
ISSN
4
3
2377-3766
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Robert Penicka1338.06
Jan Faigl233642.34
Martin Saska326634.01