Distributed motion planning algorithms for a collection of vehicles

Unmanned Vehicles (UVs) currently perform a variety of tasks critical to a military mission. In future, they are envisioned to have the ability to accomplish a mission co-operatively and effectively with limited fuel onboard. In particular, they must search for targets, classify the potential target...

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Main Author: Pargaonkar, Sudhir Sharadrao
Other Authors: Swaroop, Barbha
Format: Others
Language:en_US
Published: Texas A&M University 2004
Subjects:
Online Access:http://hdl.handle.net/1969.1/164
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spelling ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-1642013-01-08T10:37:14ZDistributed motion planning algorithms for a collection of vehiclesPargaonkar, Sudhir SharadraoMotion planningUnmanned vehiclesUnmanned Vehicles (UVs) currently perform a variety of tasks critical to a military mission. In future, they are envisioned to have the ability to accomplish a mission co-operatively and effectively with limited fuel onboard. In particular, they must search for targets, classify the potential targets detected, attack the classified targets and perform an assessment of the damage done to the targets. In some cases, UVs are themselves munitions. The targets considered in this thesis are stationary. The problem considered in this thesis, referred to as the UV problem, is the allotment of tasks to each UV along with the sequence in which they must be performed so that a maximum number of tasks are accomplished collectively. The maneuverability constraints on the UV are accounted for by treating them as Dubin's vehicles. Since the UVs considered are disposable with life spans governed by their fuel capacity, it is imperative to use their life as efficiently as possible. Thus, we need to develop a fuel-optimal (equivalently, distance optimal) motion plan for the collection of UVs. As the number of tasks to be performed and the number of vehicles performing these tasks grow, the number of ways in which the set of tasks can be distributed among the UVs increases combinatorially. The tasks a UV is required to perform are also subject to timing constraints. A UV cannot perform certain tasks before completing others. We consider a simplified version of the UV problem and do not take into account the timing constraints on the tasks to be performed on targets. We use linear programming and graph theory to find a solution to this simplified UV problem; in the graph theory approach, we develop an algorithm which is a generalization of the solution procedures available to solve the Traveling Salesman Problem (TSP). We provide an example UV problem illustrating the solution procedure developed in this thesis.Texas A&M UniversitySwaroop, Barbha2004-09-30T01:44:27Z2004-09-30T01:44:27Z2003-122004-09-30T01:44:27ZElectronic Thesistext220164 bytes21783 bytes47757 byteselectronicapplication/pdfapplication/octet-streamtext/plainborn digitalhttp://hdl.handle.net/1969.1/164en_US
collection NDLTD
language en_US
format Others
sources NDLTD
topic Motion planning
Unmanned vehicles
spellingShingle Motion planning
Unmanned vehicles
Pargaonkar, Sudhir Sharadrao
Distributed motion planning algorithms for a collection of vehicles
description Unmanned Vehicles (UVs) currently perform a variety of tasks critical to a military mission. In future, they are envisioned to have the ability to accomplish a mission co-operatively and effectively with limited fuel onboard. In particular, they must search for targets, classify the potential targets detected, attack the classified targets and perform an assessment of the damage done to the targets. In some cases, UVs are themselves munitions. The targets considered in this thesis are stationary. The problem considered in this thesis, referred to as the UV problem, is the allotment of tasks to each UV along with the sequence in which they must be performed so that a maximum number of tasks are accomplished collectively. The maneuverability constraints on the UV are accounted for by treating them as Dubin's vehicles. Since the UVs considered are disposable with life spans governed by their fuel capacity, it is imperative to use their life as efficiently as possible. Thus, we need to develop a fuel-optimal (equivalently, distance optimal) motion plan for the collection of UVs. As the number of tasks to be performed and the number of vehicles performing these tasks grow, the number of ways in which the set of tasks can be distributed among the UVs increases combinatorially. The tasks a UV is required to perform are also subject to timing constraints. A UV cannot perform certain tasks before completing others. We consider a simplified version of the UV problem and do not take into account the timing constraints on the tasks to be performed on targets. We use linear programming and graph theory to find a solution to this simplified UV problem; in the graph theory approach, we develop an algorithm which is a generalization of the solution procedures available to solve the Traveling Salesman Problem (TSP). We provide an example UV problem illustrating the solution procedure developed in this thesis.
author2 Swaroop, Barbha
author_facet Swaroop, Barbha
Pargaonkar, Sudhir Sharadrao
author Pargaonkar, Sudhir Sharadrao
author_sort Pargaonkar, Sudhir Sharadrao
title Distributed motion planning algorithms for a collection of vehicles
title_short Distributed motion planning algorithms for a collection of vehicles
title_full Distributed motion planning algorithms for a collection of vehicles
title_fullStr Distributed motion planning algorithms for a collection of vehicles
title_full_unstemmed Distributed motion planning algorithms for a collection of vehicles
title_sort distributed motion planning algorithms for a collection of vehicles
publisher Texas A&M University
publishDate 2004
url http://hdl.handle.net/1969.1/164
work_keys_str_mv AT pargaonkarsudhirsharadrao distributedmotionplanningalgorithmsforacollectionofvehicles
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