A batch informed sampling-based algorithm for fast anytime asymptotically-optimal motion planning in cluttered environments
•Present an anytime asymptotically-optimal motion planning algorithm.•A strategy is proposed that balances the “lazy” and “non-lazy” optimal search.•Analyze the swift convergence and computational complexity for the algorithm.•The proposed algorithm is comprehensively evaluated by rigorous experimen...
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| Vydané v: | Expert systems with applications Ročník 144; s. 113124 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York
Elsevier Ltd
15.04.2020
Elsevier BV |
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | •Present an anytime asymptotically-optimal motion planning algorithm.•A strategy is proposed that balances the “lazy” and “non-lazy” optimal search.•Analyze the swift convergence and computational complexity for the algorithm.•The proposed algorithm is comprehensively evaluated by rigorous experiments.
Practical applications favor anytime asymptotically-optimal algorithms that find and improve an initial solution toward the optimal solution as quickly as possible due to the algorithms may be terminated at any time. We present Batch-to-batch Informed Fast Marching Tree (BBI-FMT*), an anytime asymptotically-optimal sampling-based algorithm that is designed for solving complex motion planning problems. The proposed algorithm has the ability to fast find an initial low-cost solution by the batch sampling-based incremental search and the “lazy” optimal search, then it employs the batch informed sampling-based incremental search and the anytime optimal search to quickly improve the tree and achieve the optimal solution. The proposed anytime optimal search strategy integrates the “lazy” and “non-lazy” optimal search to efficiently improve the tree to the minimum-cost spanning tree in cluttered environments. This paper theoretically analyzes the proposed algorithm in depth and evaluates it by numerical experiments under a few challenging scenarios. The experimental results show that BBI-FMT* outperforms the state-of-the-art algorithms in the self-adaptability, robustness, convergence rate, and success rate of the planning. The proposed algorithm can be widely applied to intelligent robots with expert systems to improve the efficiency and stability of the motion planning and navigation modules which are the core modules in the expert systems. |
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| AbstractList | Practical applications favor anytime asymptotically-optimal algorithms that find and improve an initial solution toward the optimal solution as quickly as possible due to the algorithms may be terminated at any time. We present Batch-to-batch Informed Fast Marching Tree (BBI-FMT*), an anytime asymptotically-optimal sampling-based algorithm that is designed for solving complex motion planning problems. The proposed algorithm has the ability to fast find an initial low-cost solution by the batch sampling-based incremental search and the "lazy" optimal search, then it employs the batch informed sampling-based incremental search and the anytime optimal search to quickly improve the tree and achieve the optimal solution. The proposed anytime optimal search strategy integrates the "lazy" and "non-lazy" optimal search to efficiently improve the tree to the minimum-cost spanning tree in cluttered environments. This paper theoretically analyzes the proposed algorithm in depth and evaluates it by numerical experiments under a few challenging scenarios. The experimental results show that BBI-FMT* outperforms the state-of-the-art algorithms in the self-adaptability, robustness, convergence rate, and success rate of the planning. The proposed algorithm can be widely applied to intelligent robots with expert systems to improve the efficiency and stability of the motion planning and navigation modules which are the core modules in the expert systems. •Present an anytime asymptotically-optimal motion planning algorithm.•A strategy is proposed that balances the “lazy” and “non-lazy” optimal search.•Analyze the swift convergence and computational complexity for the algorithm.•The proposed algorithm is comprehensively evaluated by rigorous experiments. Practical applications favor anytime asymptotically-optimal algorithms that find and improve an initial solution toward the optimal solution as quickly as possible due to the algorithms may be terminated at any time. We present Batch-to-batch Informed Fast Marching Tree (BBI-FMT*), an anytime asymptotically-optimal sampling-based algorithm that is designed for solving complex motion planning problems. The proposed algorithm has the ability to fast find an initial low-cost solution by the batch sampling-based incremental search and the “lazy” optimal search, then it employs the batch informed sampling-based incremental search and the anytime optimal search to quickly improve the tree and achieve the optimal solution. The proposed anytime optimal search strategy integrates the “lazy” and “non-lazy” optimal search to efficiently improve the tree to the minimum-cost spanning tree in cluttered environments. This paper theoretically analyzes the proposed algorithm in depth and evaluates it by numerical experiments under a few challenging scenarios. The experimental results show that BBI-FMT* outperforms the state-of-the-art algorithms in the self-adaptability, robustness, convergence rate, and success rate of the planning. The proposed algorithm can be widely applied to intelligent robots with expert systems to improve the efficiency and stability of the motion planning and navigation modules which are the core modules in the expert systems. |
| ArticleNumber | 113124 |
| Author | Yan, Yunhui Xu, Jing Song, Kechen Dong, Hongwen |
| Author_xml | – sequence: 1 givenname: Jing orcidid: 0000-0001-6257-8770 surname: Xu fullname: Xu, Jing email: 1610099@stu.neu.edu.cn – sequence: 2 givenname: Kechen orcidid: 0000-0002-7636-3460 surname: Song fullname: Song, Kechen email: songkc@me.neu.edu.cn – sequence: 3 givenname: Hongwen surname: Dong fullname: Dong, Hongwen email: 1810108@stu.neu.edu.cn – sequence: 4 givenname: Yunhui orcidid: 0000-0001-7121-2367 surname: Yan fullname: Yan, Yunhui email: yanyh@mail.neu.edu.cn |
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| Cites_doi | 10.1016/j.oceaneng.2018.09.016 10.1126/science.153.3731.34 10.1109/TSSC.1968.300136 10.1109/TRO.2018.2830331 10.1089/soro.2017.0009 10.1177/0278364918779555 10.1090/S0002-9904-1954-09848-8 10.1016/j.aej.2018.10.011 10.1016/j.eswa.2019.01.032 10.1177/0278364915616866 10.1177/0278364915577958 10.1109/MRA.2012.2205651 10.1145/359156.359164 10.1007/BF01386390 10.1177/027836402320556421 10.1016/j.eswa.2018.01.035 10.1016/j.robot.2018.06.013 10.1109/ROBOT.1996.509171 10.1109/ACCESS.2018.2871222 10.1177/02783640122067453 10.1002/rob.21686 10.1088/1748-3190/aaeb13 10.1109/ACCESS.2014.2302442 10.1177/0278364911406761 10.1016/j.robot.2017.05.007 |
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| Keywords | Motion planning Asymptotic optimality Optimal path planning Anytime algorithm |
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| References | Dijkstra (bib0006) 1959; 1 Oh, Sohn, Jang, Jun, Cho (bib0021) 2017; 34 Tahir, Qureshi, Ayaz, Nawaz (bib0027) 2018; 108 Troy, Shawna, Amato (bib0028) 2018; 37 Salzman, Halperin (bib0023) 2015 Wan, Zhang, Vahidi (bib0029) 2017 Gammell, Barfoot, Srinivasa (bib0009) 2018; 34 Alejandro, Juan, Manuel, Antonio (bib0001) 2018; 99 Hsu, Kindel, Latombe, Rock (bib0011) 2002; 21 LaValle, Kuffner Jr (bib0017) 2001; 20 Bellman (bib0004) 1966; 153 Starek, Gomez, Schmerling, Janson, Moreno, Pavone (bib0025) 2015 Zhang, Wang, Zheng, Yu (bib0031) 2018; 6 Deng, Xin, Zhong, Mistry (bib0005) 2017; 95 Sucan, Moll, Kavraki (bib0026) 2012; 19 Karaman, Frazzoli (bib0015) 2011; 30 Mohamed, Elgamal, Elsharkawy (bib0020) 2018; 57 Alterovitz, Patil, Derbakova (bib0002) 2011 Janson, Schmerling, Clark, Pavone (bib0013) 2015; 34 Kavraki, Svestka, Latombe, Overmars (bib0016) 1996; 12 Perez, Karaman, Shkolnik, Frazzoli, Teller, Walter (bib0022) 2011 Singh, Sharma, Sutton, Hatton, Khan (bib0024) 2018; 169 Lozano-Pérez, Wesley (bib0018) 1979; 22 Hart, Nilsson, Raphael (bib0010) 1968; 4 Ferguson, Stentz (bib0008) 2007 Elbanhawi, Simic (bib0007) 2014; 2 Martín, Barrientos, del Cerro (bib0019) 2018; 5 Jeong, Lee, Kim (bib0014) 2019; 123 Bellman (bib0003) 1954; 60 Zhang, Cheng, Zhao (bib0030) 2018; 14 Huynh, Karaman, Frazzoli (bib0012) 2016; 35 Troy (10.1016/j.eswa.2019.113124_bib0028) 2018; 37 Huynh (10.1016/j.eswa.2019.113124_bib0012) 2016; 35 Perez (10.1016/j.eswa.2019.113124_sbref0022) 2011 Jeong (10.1016/j.eswa.2019.113124_bib0014) 2019; 123 LaValle (10.1016/j.eswa.2019.113124_bib0017) 2001; 20 Sucan (10.1016/j.eswa.2019.113124_bib0026) 2012; 19 Elbanhawi (10.1016/j.eswa.2019.113124_bib0007) 2014; 2 Mohamed (10.1016/j.eswa.2019.113124_bib0020) 2018; 57 Alterovitz (10.1016/j.eswa.2019.113124_bib0002) 2011 Salzman (10.1016/j.eswa.2019.113124_bib0023) 2015 Zhang (10.1016/j.eswa.2019.113124_bib0030) 2018; 14 Alejandro (10.1016/j.eswa.2019.113124_bib0001) 2018; 99 Hart (10.1016/j.eswa.2019.113124_bib0010) 1968; 4 Janson (10.1016/j.eswa.2019.113124_bib0013) 2015; 34 Martín (10.1016/j.eswa.2019.113124_bib0019) 2018; 5 Deng (10.1016/j.eswa.2019.113124_bib0005) 2017; 95 Bellman (10.1016/j.eswa.2019.113124_bib0003) 1954; 60 Bellman (10.1016/j.eswa.2019.113124_bib0004) 1966; 153 Tahir (10.1016/j.eswa.2019.113124_bib0027) 2018; 108 Ferguson (10.1016/j.eswa.2019.113124_sbref0008) 2007 Hsu (10.1016/j.eswa.2019.113124_bib0011) 2002; 21 Kavraki (10.1016/j.eswa.2019.113124_bib0016) 1996; 12 Starek (10.1016/j.eswa.2019.113124_bib0025) 2015 Gammell (10.1016/j.eswa.2019.113124_bib0009) 2018; 34 Lozano-Pérez (10.1016/j.eswa.2019.113124_bib0018) 1979; 22 Zhang (10.1016/j.eswa.2019.113124_bib0031) 2018; 6 Dijkstra (10.1016/j.eswa.2019.113124_bib0006) 1959; 1 Oh (10.1016/j.eswa.2019.113124_bib0021) 2017; 34 Wan (10.1016/j.eswa.2019.113124_bib0029) 2017 Singh (10.1016/j.eswa.2019.113124_bib0024) 2018; 169 Karaman (10.1016/j.eswa.2019.113124_bib0015) 2011; 30 |
| References_xml | – volume: 34 start-page: 966 year: 2018 end-page: 984 ident: bib0009 article-title: Informed sampling for asymptotically optimal path planning publication-title: IEEE Transactions on Robotics – volume: 30 start-page: 846 year: 2011 end-page: 894 ident: bib0015 article-title: Sampling-based algorithms for optimal motion planning publication-title: The International Journal of Robotics Research – volume: 5 start-page: 242 year: 2018 end-page: 257 ident: bib0019 article-title: The natural-CCD algorithm, a novel method to solve the inverse kinematics of hyper-redundant and soft robots publication-title: Soft Robotics – start-page: 4167 year: 2015 end-page: 4172 ident: bib0023 article-title: Asymptotically-optimal motion planning using publication-title: Proceedings of the IEEE international conference on robotics & automation – start-page: 4307 year: 2011 end-page: 4313 ident: bib0022 article-title: Asymptotically-optimal path planning for manipulation using incremental sampling-based algorithms publication-title: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems – start-page: 2072 year: 2015 end-page: 2078 ident: bib0025 article-title: An asymptotically-optimal sampling-based algorithm for bi-directional motion planning publication-title: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS) – volume: 108 start-page: 13 year: 2018 end-page: 27 ident: bib0027 article-title: Potentially guided bidirecti-onalized RRT* for fast optimal path planning in cluttered environments publication-title: Robotics Autonomous Systems – volume: 20 start-page: 378 year: 2001 end-page: 400 ident: bib0017 article-title: Randomized kinodynamic planning publication-title: The International Journal of Robotics Research – volume: 169 start-page: 187 year: 2018 end-page: 201 ident: bib0024 article-title: A constrained A* approach towards optimal path planning for an unmanned surface vehicle in a mar-itime environment containing dynamic obstacles and ocean currents publication-title: Ocean Engineering – volume: 2 start-page: 56 year: 2014 end-page: 77 ident: bib0007 article-title: Sampling-based robot motion planning: A review publication-title: IEEE Access : Practical Innovations, Open Solutions – volume: 153 start-page: 34 year: 1966 end-page: 37 ident: bib0004 article-title: Dynamic programming publication-title: Science (New York, N.Y.) – volume: 57 start-page: 4103 year: 2018 end-page: 4112 ident: bib0020 article-title: Dynamic analysis with optimum trajectory planning of multiple degree-of-freedom surgical micro-robot publication-title: Alexandria Engineering Journal – start-page: 1310 year: 2007 end-page: 1315 ident: bib0008 article-title: Anytime, dynamic planning in high-dimensional search spaces publication-title: Proceedings IEEE international conference on robotics and automation – volume: 4 start-page: 100 year: 1968 end-page: 107 ident: bib0010 article-title: A formal basis for the heuristic determination of minimum cost paths publication-title: IEEE Transactions on Systems Science Cybernetics – volume: 99 start-page: 141 year: 2018 end-page: 154 ident: bib0001 article-title: Quad-RRT: A real-time GPU-based global path planner in large-scale real environments publication-title: Expert Systems with Applications – volume: 12 year: 1996 ident: bib0016 article-title: Probabilistic roadmaps for path planning in high-dimensional configuration spaces publication-title: IEEE Transacrions on Robotics Automation – volume: 21 start-page: 233 year: 2002 end-page: 255 ident: bib0011 article-title: Randomized kinodynamic motion planning with moving obstacles publication-title: The International Journal of Robotics Research – start-page: 3706 year: 2011 end-page: 3712 ident: bib0002 article-title: Rapidly-exploring roadmaps: Weighing exploration vs. refinement in optimal motion planning publication-title: international conference on robotics and automation – volume: 37 start-page: 779 year: 2018 end-page: 817 ident: bib0028 article-title: Sampling-based motion planning with reachable volumes for high-degree-of-freedom manipulators publication-title: The International Journal of Robotics Research – volume: 22 start-page: 560 year: 1979 end-page: 570 ident: bib0018 article-title: An algorithm for planning collision-free paths among polyhedral obstacles publication-title: Communications of the ACM – volume: 14 start-page: 1 year: 2018 end-page: 13 ident: bib0030 article-title: Optimal trajectory generation for time-to-contact based aerial robotic perching publication-title: Bioinspiration Biomimetics – volume: 6 start-page: 53296 year: 2018 end-page: 53306 ident: bib0031 article-title: Path planning of industrial robot Based on improved rrt algorithm in complex environments publication-title: IEEE Access : Practical Innovations, Open Solutions – volume: 123 start-page: 82 year: 2019 end-page: 90 ident: bib0014 article-title: Quick-RRT*: Triangular inequality-based implementation of RRT* with improved initial solution and convergence rate publication-title: Expert Systems with Applications – volume: 19 start-page: 72 year: 2012 end-page: 82 ident: bib0026 article-title: The open motion planning library publication-title: IEEE Robotics Automation Magazine – volume: 60 start-page: 503 year: 1954 end-page: 515 ident: bib0003 article-title: The theory of dynamic programming publication-title: Bulletin of the American Mathematical Society – volume: 34 start-page: 874 year: 2017 end-page: 896 ident: bib0021 article-title: Technical overview of team DRC‐Hubo@ UNLV's approach to the 2015 darpa robotics challenge finals publication-title: Journal of Field Robotics – volume: 1 start-page: 269 year: 1959 end-page: 271 ident: bib0006 article-title: A note on two problems in connexion with graphs publication-title: Numerische mathematik – volume: 34 start-page: 883 year: 2015 end-page: 921 ident: bib0013 article-title: Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions publication-title: The International Journal of Robotics Research – start-page: 1 year: 2017 end-page: 9 ident: bib0029 article-title: Probabilistic anticipation and control in autonomous car following publication-title: IEEE Transactions on Control Systems Technology – volume: 95 start-page: 13 year: 2017 end-page: 24 ident: bib0005 article-title: Gait and trajectory rolling planning and control of hexapod robots for disaster rescue applications publication-title: Robotics Autonomous Systems – volume: 35 start-page: 305 year: 2016 end-page: 333 ident: bib0012 article-title: An incremental sampling-based algorithm for stochastic optimal control publication-title: The International Journal of Robotics Research – volume: 169 start-page: 187 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0024 article-title: A constrained A* approach towards optimal path planning for an unmanned surface vehicle in a mar-itime environment containing dynamic obstacles and ocean currents publication-title: Ocean Engineering doi: 10.1016/j.oceaneng.2018.09.016 – volume: 153 start-page: 34 issue: 3731 year: 1966 ident: 10.1016/j.eswa.2019.113124_bib0004 article-title: Dynamic programming publication-title: Science (New York, N.Y.) doi: 10.1126/science.153.3731.34 – volume: 4 start-page: 100 issue: 2 year: 1968 ident: 10.1016/j.eswa.2019.113124_bib0010 article-title: A formal basis for the heuristic determination of minimum cost paths publication-title: IEEE Transactions on Systems Science Cybernetics doi: 10.1109/TSSC.1968.300136 – volume: 34 start-page: 966 issue: 4 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0009 article-title: Informed sampling for asymptotically optimal path planning publication-title: IEEE Transactions on Robotics doi: 10.1109/TRO.2018.2830331 – volume: 5 start-page: 242 issue: 3 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0019 article-title: The natural-CCD algorithm, a novel method to solve the inverse kinematics of hyper-redundant and soft robots publication-title: Soft Robotics doi: 10.1089/soro.2017.0009 – volume: 37 start-page: 779 issue: 7 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0028 article-title: Sampling-based motion planning with reachable volumes for high-degree-of-freedom manipulators publication-title: The International Journal of Robotics Research doi: 10.1177/0278364918779555 – volume: 60 start-page: 503 issue: 6 year: 1954 ident: 10.1016/j.eswa.2019.113124_bib0003 article-title: The theory of dynamic programming publication-title: Bulletin of the American Mathematical Society doi: 10.1090/S0002-9904-1954-09848-8 – volume: 57 start-page: 4103 issue: 4 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0020 article-title: Dynamic analysis with optimum trajectory planning of multiple degree-of-freedom surgical micro-robot publication-title: Alexandria Engineering Journal doi: 10.1016/j.aej.2018.10.011 – start-page: 1310 year: 2007 ident: 10.1016/j.eswa.2019.113124_sbref0008 article-title: Anytime, dynamic planning in high-dimensional search spaces – volume: 123 start-page: 82 year: 2019 ident: 10.1016/j.eswa.2019.113124_bib0014 article-title: Quick-RRT*: Triangular inequality-based implementation of RRT* with improved initial solution and convergence rate publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2019.01.032 – volume: 35 start-page: 305 issue: 4 year: 2016 ident: 10.1016/j.eswa.2019.113124_bib0012 article-title: An incremental sampling-based algorithm for stochastic optimal control publication-title: The International Journal of Robotics Research doi: 10.1177/0278364915616866 – volume: 34 start-page: 883 issue: 7 year: 2015 ident: 10.1016/j.eswa.2019.113124_bib0013 article-title: Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions publication-title: The International Journal of Robotics Research doi: 10.1177/0278364915577958 – volume: 19 start-page: 72 issue: 4 year: 2012 ident: 10.1016/j.eswa.2019.113124_bib0026 article-title: The open motion planning library publication-title: IEEE Robotics Automation Magazine doi: 10.1109/MRA.2012.2205651 – volume: 22 start-page: 560 issue: 10 year: 1979 ident: 10.1016/j.eswa.2019.113124_bib0018 article-title: An algorithm for planning collision-free paths among polyhedral obstacles publication-title: Communications of the ACM doi: 10.1145/359156.359164 – start-page: 4167 year: 2015 ident: 10.1016/j.eswa.2019.113124_bib0023 article-title: Asymptotically-optimal motion planning using lower bounds on cost – volume: 1 start-page: 269 issue: 1 year: 1959 ident: 10.1016/j.eswa.2019.113124_bib0006 article-title: A note on two problems in connexion with graphs publication-title: Numerische mathematik doi: 10.1007/BF01386390 – volume: 21 start-page: 233 issue: 3 year: 2002 ident: 10.1016/j.eswa.2019.113124_bib0011 article-title: Randomized kinodynamic motion planning with moving obstacles publication-title: The International Journal of Robotics Research doi: 10.1177/027836402320556421 – volume: 99 start-page: 141 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0001 article-title: Quad-RRT: A real-time GPU-based global path planner in large-scale real environments publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2018.01.035 – start-page: 4307 year: 2011 ident: 10.1016/j.eswa.2019.113124_sbref0022 article-title: Asymptotically-optimal path planning for manipulation using incremental sampling-based algorithms – volume: 108 start-page: 13 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0027 article-title: Potentially guided bidirecti-onalized RRT* for fast optimal path planning in cluttered environments publication-title: Robotics Autonomous Systems doi: 10.1016/j.robot.2018.06.013 – volume: 12 issue: 4 year: 1996 ident: 10.1016/j.eswa.2019.113124_bib0016 article-title: Probabilistic roadmaps for path planning in high-dimensional configuration spaces publication-title: IEEE Transacrions on Robotics Automation doi: 10.1109/ROBOT.1996.509171 – volume: 6 start-page: 53296 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0031 article-title: Path planning of industrial robot Based on improved rrt algorithm in complex environments publication-title: IEEE Access : Practical Innovations, Open Solutions doi: 10.1109/ACCESS.2018.2871222 – volume: 20 start-page: 378 issue: 5 year: 2001 ident: 10.1016/j.eswa.2019.113124_bib0017 article-title: Randomized kinodynamic planning publication-title: The International Journal of Robotics Research doi: 10.1177/02783640122067453 – volume: 34 start-page: 874 issue: 5 year: 2017 ident: 10.1016/j.eswa.2019.113124_bib0021 article-title: Technical overview of team DRC‐Hubo@ UNLV's approach to the 2015 darpa robotics challenge finals publication-title: Journal of Field Robotics doi: 10.1002/rob.21686 – volume: 14 start-page: 1 issue: 1 year: 2018 ident: 10.1016/j.eswa.2019.113124_bib0030 article-title: Optimal trajectory generation for time-to-contact based aerial robotic perching publication-title: Bioinspiration Biomimetics doi: 10.1088/1748-3190/aaeb13 – volume: 2 start-page: 56 year: 2014 ident: 10.1016/j.eswa.2019.113124_bib0007 article-title: Sampling-based robot motion planning: A review publication-title: IEEE Access : Practical Innovations, Open Solutions doi: 10.1109/ACCESS.2014.2302442 – volume: 30 start-page: 846 issue: 7 year: 2011 ident: 10.1016/j.eswa.2019.113124_bib0015 article-title: Sampling-based algorithms for optimal motion planning publication-title: The International Journal of Robotics Research doi: 10.1177/0278364911406761 – volume: 95 start-page: 13 year: 2017 ident: 10.1016/j.eswa.2019.113124_bib0005 article-title: Gait and trajectory rolling planning and control of hexapod robots for disaster rescue applications publication-title: Robotics Autonomous Systems doi: 10.1016/j.robot.2017.05.007 – start-page: 1 issue: 99 year: 2017 ident: 10.1016/j.eswa.2019.113124_bib0029 article-title: Probabilistic anticipation and control in autonomous car following publication-title: IEEE Transactions on Control Systems Technology – start-page: 3706 year: 2011 ident: 10.1016/j.eswa.2019.113124_bib0002 article-title: Rapidly-exploring roadmaps: Weighing exploration vs. refinement in optimal motion planning – start-page: 2072 year: 2015 ident: 10.1016/j.eswa.2019.113124_bib0025 article-title: An asymptotically-optimal sampling-based algorithm for bi-directional motion planning publication-title: IEEE |
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| Snippet | •Present an anytime asymptotically-optimal motion planning algorithm.•A strategy is proposed that balances the “lazy” and “non-lazy” optimal search.•Analyze... Practical applications favor anytime asymptotically-optimal algorithms that find and improve an initial solution toward the optimal solution as quickly as... |
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| SubjectTerms | Algorithms Anytime algorithm Asymptotic optimality Asymptotic properties Cost analysis Expert systems Graph theory Modules Motion planning Motion stability Optimal path planning Robustness (mathematics) Sampling Searching |
| Title | A batch informed sampling-based algorithm for fast anytime asymptotically-optimal motion planning in cluttered environments |
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