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Memory-Constrained Pathfinding Algorithms for Partially-Known Environments University of Windsor Scholarship at UWindsor Electronic Theses and Dissertations Theses, Dissertations, and Major Papers 2007 Memory-constrained pathfinding algorithms for partially-known environments Denton Cockburn University of Windsor Follow this and additional works at: https://scholar.uwindsor.ca/etd Recommended Citation Cockburn, Denton, "Memory-constrained pathfinding algorithms for partially-known environments" (2007). Electronic Theses and Dissertations. 4672. https://scholar.uwindsor.ca/etd/4672 This online database contains the full-text of PhD dissertations and Masters’ theses of University of Windsor students from 1954 forward. These documents are made available for personal study and research purposes only, in accordance with the Canadian Copyright Act and the Creative Commons license—CC BY-NC-ND (Attribution, Non-Commercial, No Derivative Works). Under this license, works must always be attributed to the copyright holder (original author), cannot be used for any commercial purposes, and may not be altered. Any other use would require the permission of the copyright holder. Students may inquire about withdrawing their dissertation and/or thesis from this database. For additional inquiries, please contact the repository administrator via email ([email protected]) or by telephone at 519-253-3000ext. 3208. Memory-Constrained Pathfinding Algorithms for Partially-Known Environments by Denton Cockbum A Thesis Submitted to the Faculty of Graduate Studies through The School of Computer Science in Partial Fulfillment of the Requirements for the Degree of Master o f Science at the University of Windsor Windsor, Ontario, Canada 2007 © Denton Cockbum 2007 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Library and Bibliotheque et Archives Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition 395 Wellington Street 395, rue Wellington Ottawa ON K1A 0N4 Ottawa ON K1A 0N4 Canada Canada Your file Votre reference ISBN: 978-0-494-34975-5 Our file Notre reference ISBN: 978-0-494-34975-5 NOTICE: AVIS: The author has granted a non­ L'auteur a accorde une licence non exclusive exclusive license allowing Library permettant a la Bibliotheque et Archives and Archives Canada to reproduce,Canada de reproduire, publier, archiver, publish, archive, preserve, conserve,sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par I'lnternet, preter, telecommunication or on the Internet,distribuer et vendre des theses partout dans loan, distribute and sell theses le monde, a des fins commerciales ou autres, worldwide, for commercial or non­ sur support microforme, papier, electronique commercial purposes, in microform,et/ou autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in et des droits moraux qui protege cette these. this thesis. Neither the thesis Ni la these ni des extraits substantiels de nor substantial extracts from it celle-ci ne doivent etre imprimes ou autrement may be printed or otherwise reproduits sans son autorisation. reproduced without the author's permission. In compliance with the Canadian Conformement a la loi canadienne Privacy Act some supporting sur la protection de la vie privee, forms may have been removed quelques formulaires secondaires from this thesis. ont ete enleves de cette these. While these forms may be includedBien que ces formulaires in the document page count, aient inclus dans la pagination, their removal does not represent il n'y aura aucun contenu manquant. any loss of content from the thesis. i * i Canada Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT Pathfmding is the search for a goal state given a start state, within either static Or dynamic environments. Many pathfmding algorithms exist, including established algorithms such as A*, SMA:*, and D*. These algorithms all provide optimal solution paths, using all available memory. Consequently, Algorithms such as A* and D* are known to be inefficient in terms of memory space usage. SMA* and similar algorithms provide a means by which optimal solution paths can be found while being memory efficient. SMA* and such algorithms are restricted to static environments, in which state traversal costs never change. This is a severe limitation, as one of the primary fields for search algorithms are games, many of which involve dynamic environments. Presented in this paper is a dynamic variant of the established D* Lite algorithm, that is able to provide an optimal solution path, if given sufficient memory, while using as little memory as possible. It is also the case that in some areas, an optimal solution is not needed. This may be the case for robotics. Many algorithms already exist in this area, such as Anytime algorithms for time-limited searches. Real-Time algorithms for when the agent needs to move while planning its path. Also presented is an algorithm for real-time planning when an agent does not have a priori knowledge of the environment, and also limited memory capacity. This algorithm sacrifices optimality, but in turn is highly memory efficient, even in comparison to other algorithms designed for memory efficiency. iii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. DEDICATION I would like to dedicate this work to my two sets of parents. I am fortunate to have two great families that love me so much. My dad and stepmother, thank you so much for all that you have put into me and my education. I couldn't be who I am today without you. My mother and my stepfather, thank you for helping me be the man I am today. When I get stressed with the winter months and the school burnout, I always have a tropical home to return to. I'd like to thank you all for all that you have done for me, I love you. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ACKNOWLEDGEMENTS I would like to thank first of all my advisor Dr. Kobti. Your guidance has helped me through times when I doubted myself. You have also been an inspiration in showing me that I can continue my education to even higher heights. I'd also like to thank Dr. Goodwin. > Your class is what started me along this research area. Thank you for making your class fun to be in and learn from. Also thank you for the advice and patience you have given and shown. I'd also like to thank Dr. Ngom. Even though I wasn't a student of yours, you spent a lot of your time advising me. I thank you for suggesting I continue with this research area. Finally, I'd like to thank the ladies in the computer science office. You made handling school bureaucracy a breeze. v Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table of Contents ABSTRACT...........................................................................................................................................................3 DEDICATION.............................................................. 4 ACKNOWLEDGEMENTS .........................................................................................................................5 Chapter 1: Introduction.................................................;............. 1 1.1 Background....................................................................................... 1 1.2 Motivation.................................................... 1 1.3 Thesis Contribution................................................................................................................................... 3 1.4 Thesis Organization......................................... 3 Chapter 2: Review of Literature....................................................................... 5 2.1 A* .................................................................................................................................................................5 2.2 SMA* ............................................................................................................................. 7 2.3 LPA* ................................................................................. ,.........................................................................7 2.4 Focused D*................................................................................................................................................. 9 2.5 D* Lite ........................................................................................................ !...............................................9 2.6 Anytime Repairing A* ............................................................................................................................ 10 2.7 Anytime D* ...............................................................................................................................................11 2.8 Adaptive A*..............................................................................................................................................12 2.9 Fringe Saving A*................................................................................................... 13 2.10 Delayed D*............................................................................................................................................. 14 Chapter 3: Range-Limited A*...........................................................................................................................
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