Path/Action Planning for a Mobile Robot

This thesis consists of two parts united by the theme of path/action planning for a mobile robot. Part I presents the Second Opinion Planner (SOP), and Part II presents a new paradigm for navigating, growing, and planning on a Network of Reusable Paths (NRP). Path/action planning is common to both p...

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Bibliographic Details
Main Author: Stenning, Braden Edward
Other Authors: Barfoot, Timothy D.
Language:en_ca
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/1807/36006
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-OTU.1807-360062013-11-02T03:43:08ZPath/Action Planning for a Mobile RobotStenning, Braden Edwardmobile robotautonomyfield roboticspath planning0538RoboticsThis thesis consists of two parts united by the theme of path/action planning for a mobile robot. Part I presents the Second Opinion Planner (SOP), and Part II presents a new paradigm for navigating, growing, and planning on a Network of Reusable Paths (NRP). Path/action planning is common to both parts in that the planning algorithm must choose the terrain assessment or localization technique at the path-planning stage. Terrain-assessment algorithms follow the trend of low-fidelity at low-cost and high-fidelity at high-cost. Using a high-fidelity method on all the raw terrain data can drastically increase a robot's total path cost (cost of driving, planning, and doing the terrain assessment). SOP is a path-planning algorithm that uses a hierarchy of terrain-assessment methods, from low-fidelity to high-fidelity, and seeks to limit high-cost assessment to areas where it is beneficial. The decision to assess some terrain with a higher-fidelity method is made considering potential path benefits and the cost of assessment. SOP provides a means to triage large amounts of terrain data. The system is demonstrated on simulated problems and in real terrain from an experimental field test carried out on Devon Island, Canada. The SOP plans are quite close to the minimum possible cost. Growing a NRP is an approach to navigation that allows a mobile robot to autonomously explore unmapped, GPS-denied environments. This new paradigm results in closer goal acquisition and a more robust approach to exploration with a mobile robot, when compared to a classic approach to guidance, navigation, and control. A NRP is a simple Simultaneous Localization And Mapping system that can be shown to be a physical embodiment of a Rapidly-exploring Random Tree planner. Simulation results are presented, as well as the results from two different robotic test systems that were tested in planetary analogue environments. NRP offers benefits to planetary exploration by allowing a rover to be used for the parallel scientific investigations. This increases the number of sites that can be investigated in a short time, as compared to a serial approach to exploration. Two mock missions were carried out at planetary analogue sites.Barfoot, Timothy D.2013-062013-08-13T15:08:34ZNO_RESTRICTION2013-08-13T15:08:34Z2013-08-13Thesishttp://hdl.handle.net/1807/36006en_ca
collection NDLTD
language en_ca
sources NDLTD
topic mobile robot
autonomy
field robotics
path planning
0538
Robotics
spellingShingle mobile robot
autonomy
field robotics
path planning
0538
Robotics
Stenning, Braden Edward
Path/Action Planning for a Mobile Robot
description This thesis consists of two parts united by the theme of path/action planning for a mobile robot. Part I presents the Second Opinion Planner (SOP), and Part II presents a new paradigm for navigating, growing, and planning on a Network of Reusable Paths (NRP). Path/action planning is common to both parts in that the planning algorithm must choose the terrain assessment or localization technique at the path-planning stage. Terrain-assessment algorithms follow the trend of low-fidelity at low-cost and high-fidelity at high-cost. Using a high-fidelity method on all the raw terrain data can drastically increase a robot's total path cost (cost of driving, planning, and doing the terrain assessment). SOP is a path-planning algorithm that uses a hierarchy of terrain-assessment methods, from low-fidelity to high-fidelity, and seeks to limit high-cost assessment to areas where it is beneficial. The decision to assess some terrain with a higher-fidelity method is made considering potential path benefits and the cost of assessment. SOP provides a means to triage large amounts of terrain data. The system is demonstrated on simulated problems and in real terrain from an experimental field test carried out on Devon Island, Canada. The SOP plans are quite close to the minimum possible cost. Growing a NRP is an approach to navigation that allows a mobile robot to autonomously explore unmapped, GPS-denied environments. This new paradigm results in closer goal acquisition and a more robust approach to exploration with a mobile robot, when compared to a classic approach to guidance, navigation, and control. A NRP is a simple Simultaneous Localization And Mapping system that can be shown to be a physical embodiment of a Rapidly-exploring Random Tree planner. Simulation results are presented, as well as the results from two different robotic test systems that were tested in planetary analogue environments. NRP offers benefits to planetary exploration by allowing a rover to be used for the parallel scientific investigations. This increases the number of sites that can be investigated in a short time, as compared to a serial approach to exploration. Two mock missions were carried out at planetary analogue sites.
author2 Barfoot, Timothy D.
author_facet Barfoot, Timothy D.
Stenning, Braden Edward
author Stenning, Braden Edward
author_sort Stenning, Braden Edward
title Path/Action Planning for a Mobile Robot
title_short Path/Action Planning for a Mobile Robot
title_full Path/Action Planning for a Mobile Robot
title_fullStr Path/Action Planning for a Mobile Robot
title_full_unstemmed Path/Action Planning for a Mobile Robot
title_sort path/action planning for a mobile robot
publishDate 2013
url http://hdl.handle.net/1807/36006
work_keys_str_mv AT stenningbradenedward pathactionplanningforamobilerobot
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