Path planning for an autonomous vehicle

Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2000. === Includes bibliographical references (p. 163-164). === The desire for highly capable unmanned autonomous vehicles (UAVs), has necessitated the need for more research into the problems faced by these vehicles....

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Main Author: McKeever, Scott Douglas, 1976-
Other Authors: Michael J. Ricard and Georgia Perakis.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2005
Subjects:
Online Access:http://hdl.handle.net/1721.1/8741
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-87412019-05-02T16:25:39Z Path planning for an autonomous vehicle Path planning for a UAV McKeever, Scott Douglas, 1976- Michael J. Ricard and Georgia Perakis. Sloan School of Management. Sloan School of Management. Sloan School of Management. Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2000. Includes bibliographical references (p. 163-164). The desire for highly capable unmanned autonomous vehicles (UAVs), has necessitated the need for more research into the problems faced by these vehicles. One classic problem faced by UAVs concerns how the vehicle should traverse its environment in order to leave the current position and arrive at a desired location. The path to this goal location must maneuver the vehicle around any obstacles and reach the goal with minimal cost. A variant of this problem tasks the UAV with tracking a moving target. In this manner the UAVs trajectory is updated through time to reflect changes in the target's location. The specific mission addressed in this thesis, is the track and trail mission. This mission tasks a UAV with acquiring a target vehicle and tracking the vehicle for an indefinite period of time. The goal of this mission is not to intercept the vehicle, but to follow the target from a certain standoff distance. One can imagine many applications of this mission. One such application envisioned by the United States Navy deals with an unmanned underwater vehicle (UUV), tracking an enemy submarine. In addition, marine biologists could use such a capability to allow a UUV to follow and record valuable information on certain species. Planning these paths is conceptualized as a series of network shortest path problems. This thesis focuses on planning paths in the plane where the state of the vehicle is defined only by its position in space. In addition, a trajectory smoothing or path-smoothing component is addressed to eliminate any slope discontinuities as a result of the shortest path algorithms. A framework for the moving target shortest path problem is created. The resulting path planner is capable of performing the stated mission. A detailed simulation of the path planner operating on a UUV in an underwater environment is created in order to test the planner's performance. Different variants of the path planner are created in order to deal with different problem parameters. The resulting path planner is shown to be adaptable to these different conditions and effective at tracking a moving target. by Scott Douglas McKeever. S.M. 2005-08-23T14:55:58Z 2005-08-23T14:55:58Z 2000 2000 Thesis http://hdl.handle.net/1721.1/8741 48040832 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 164 p. 10923209 bytes 10922968 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Sloan School of Management.
spellingShingle Sloan School of Management.
McKeever, Scott Douglas, 1976-
Path planning for an autonomous vehicle
description Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2000. === Includes bibliographical references (p. 163-164). === The desire for highly capable unmanned autonomous vehicles (UAVs), has necessitated the need for more research into the problems faced by these vehicles. One classic problem faced by UAVs concerns how the vehicle should traverse its environment in order to leave the current position and arrive at a desired location. The path to this goal location must maneuver the vehicle around any obstacles and reach the goal with minimal cost. A variant of this problem tasks the UAV with tracking a moving target. In this manner the UAVs trajectory is updated through time to reflect changes in the target's location. The specific mission addressed in this thesis, is the track and trail mission. This mission tasks a UAV with acquiring a target vehicle and tracking the vehicle for an indefinite period of time. The goal of this mission is not to intercept the vehicle, but to follow the target from a certain standoff distance. One can imagine many applications of this mission. One such application envisioned by the United States Navy deals with an unmanned underwater vehicle (UUV), tracking an enemy submarine. In addition, marine biologists could use such a capability to allow a UUV to follow and record valuable information on certain species. Planning these paths is conceptualized as a series of network shortest path problems. This thesis focuses on planning paths in the plane where the state of the vehicle is defined only by its position in space. In addition, a trajectory smoothing or path-smoothing component is addressed to eliminate any slope discontinuities as a result of the shortest path algorithms. A framework for the moving target shortest path problem is created. The resulting path planner is capable of performing the stated mission. A detailed simulation of the path planner operating on a UUV in an underwater environment is created in order to test the planner's performance. Different variants of the path planner are created in order to deal with different problem parameters. The resulting path planner is shown to be adaptable to these different conditions and effective at tracking a moving target. === by Scott Douglas McKeever. === S.M.
author2 Michael J. Ricard and Georgia Perakis.
author_facet Michael J. Ricard and Georgia Perakis.
McKeever, Scott Douglas, 1976-
author McKeever, Scott Douglas, 1976-
author_sort McKeever, Scott Douglas, 1976-
title Path planning for an autonomous vehicle
title_short Path planning for an autonomous vehicle
title_full Path planning for an autonomous vehicle
title_fullStr Path planning for an autonomous vehicle
title_full_unstemmed Path planning for an autonomous vehicle
title_sort path planning for an autonomous vehicle
publisher Massachusetts Institute of Technology
publishDate 2005
url http://hdl.handle.net/1721.1/8741
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