Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems

Sundar, Kaarthik; Rathinam, Sivakumar

doi:10.1007/s10846-016-0458-5

Title: Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems

Journal Article · Mon Dec 26 00:00:00 EST 2016 · Journal of Intelligent & Robotic Systems

DOI:https://doi.org/10.1007/s10846-016-0458-5· OSTI ID:1345942

^[1]; Rathinam, Sivakumar ^[2]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Texas A & M Univ., College Station, TX (United States)

Unmanned vehicles, both aerial and ground, are being used in several monitoring applications to collect data from a set of targets. This article addresses a problem where a group of heterogeneous aerial or ground vehicles with different motion constraints located at distinct depots visit a set of targets. The vehicles also may be equipped with different sensors, and therefore, a target may not be visited by any vehicle. The objective is to find an optimal path for each vehicle starting and ending at its respective depot such that each target is visited at least once by some vehicle, the vehicle–target constraints are satisfied, and the sum of the length of the paths for all the vehicles is minimized. Two variants of this problem are formulated (one for ground vehicles and another for aerial vehicles) as mixed-integer linear programs and a branchand- cut algorithm is developed to compute an optimal solution to each of the variants. Computational results show that optimal solutions for problems involving 100 targets and 5 vehicles can be obtained within 300 seconds on average, further corroborating the effectiveness of the proposed approach.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1345942

Report Number(s):: LA-UR-16-26700

Journal Information:: Journal of Intelligent & Robotic Systems, Vol. 88, Issue 2-4; ISSN 0921-0296

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 27 works

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Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey Otto, Alena; Agatz, Niels; Campbell, James Networks, Vol. 72, Issue 4 https://doi.org/10.1002/net.21818	journal	March 2018
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Title: Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems

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