Bi-objective path planning using deterministic algorithms
Path planning has become a central problem in motion planning. The classic version of the problem aims to find an obstacle-free path with the minimum length for a given workspace containing a set of obstacles and two sources and destination points. However, some real world applications consider maxi...
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| Veröffentlicht in: | Robotics and autonomous systems Jg. 93; S. 105 - 115 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.07.2017
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| ISSN: | 0921-8890, 1872-793X |
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| Abstract | Path planning has become a central problem in motion planning. The classic version of the problem aims to find an obstacle-free path with the minimum length for a given workspace containing a set of obstacles and two sources and destination points. However, some real world applications consider maximizing the path clearance (i.e., the distance between the robot and obstacles) as the secondary objective. This bi-objective path planning problem has been studied using evolutionary and other heuristic algorithms which do not guarantee achieving Pareto optimal paths. In this paper, we first study this problem using deterministic algorithms. Next, we propose an efficient algorithm for the problem in the grid workspace. We then propose an O(n3) time algorithm for the problem under the Manhattan distance in a continuous workspace containing n vertical segments as obstacles. Finally, we show the obtained solutions are proper approximation for the problem under the Euclidean distance.
•Introducing a bi-objective length and clearance path planning (bi-PP) model.•Proposing an algorithm for solving the bi-PP in grid and finding Pareto fronts.•Proposing an algorithm for solving the bi-PP in continuous Manhattan space.•Approximating Pareto solutions of the bi-PP under the Euclidean distance. |
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| AbstractList | Path planning has become a central problem in motion planning. The classic version of the problem aims to find an obstacle-free path with the minimum length for a given workspace containing a set of obstacles and two sources and destination points. However, some real world applications consider maximizing the path clearance (i.e., the distance between the robot and obstacles) as the secondary objective. This bi-objective path planning problem has been studied using evolutionary and other heuristic algorithms which do not guarantee achieving Pareto optimal paths. In this paper, we first study this problem using deterministic algorithms. Next, we propose an efficient algorithm for the problem in the grid workspace. We then propose an O(n3) time algorithm for the problem under the Manhattan distance in a continuous workspace containing n vertical segments as obstacles. Finally, we show the obtained solutions are proper approximation for the problem under the Euclidean distance.
•Introducing a bi-objective length and clearance path planning (bi-PP) model.•Proposing an algorithm for solving the bi-PP in grid and finding Pareto fronts.•Proposing an algorithm for solving the bi-PP in continuous Manhattan space.•Approximating Pareto solutions of the bi-PP under the Euclidean distance. |
| Author | Davoodi, Mansoor |
| Author_xml | – sequence: 1 givenname: Mansoor surname: Davoodi fullname: Davoodi, Mansoor email: mdmonfared@iasbs.ac.ir organization: Department of Computer Sciences and Information Technology, Institute for Advances Studies in Basic Sciences, Zanjan, Iran |
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| CitedBy_id | crossref_primary_10_1016_j_oceaneng_2019_04_055 crossref_primary_10_1007_s12647_022_00618_6 crossref_primary_10_1007_s41870_023_01269_9 crossref_primary_10_1016_j_robot_2018_11_005 crossref_primary_10_1007_s10846_020_01196_y crossref_primary_10_1109_LRA_2018_2876888 crossref_primary_10_1007_s12647_024_00752_3 crossref_primary_10_1109_LRA_2024_3522786 crossref_primary_10_1007_s00373_023_02744_7 crossref_primary_10_1007_s10707_019_00385_8 crossref_primary_10_1088_1742_6596_2188_1_012005 crossref_primary_10_1016_j_robot_2019_02_013 |
| Cites_doi | 10.1016/S0921-8890(00)00088-9 10.1016/0020-0190(85)90044-4 10.1016/j.asoc.2012.07.023 10.1007/s00500-006-0068-4 10.1137/S0097539795289604 10.1016/j.ins.2014.10.017 10.1016/j.robot.2013.04.007 10.1177/0278364907079280 10.1016/j.robot.2013.07.012 10.1007/BF01386390 10.1007/s00500-012-0964-8 10.1016/j.asoc.2015.04.017 10.1016/j.robot.2015.06.002 10.1016/j.robot.2013.12.004 10.1016/j.eswa.2013.07.110 10.1109/TSMCC.2007.900654 10.1016/j.tcs.2005.09.022 10.1287/opre.35.1.70 |
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| Keywords | Bi-objective optimization Path planning Approximation Clearance Pareto optimal |
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