Mobile robot path planning using fuzzy enhanced improved Multi-Objective particle swarm optimization (FIMOPSO)
•Efficient algorithm is needed for cracking Car-like Robot Path Planning problems.•An Improved Multi-objective PSO algorithm is proposed and compared with MOSPEA2.•Five objective functions are considered in solving multi-objective CRPP problems.•Totally six experiments were conducted to validate the...
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| Vydané v: | Expert systems with applications Ročník 198; s. 116875 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York
Elsevier Ltd
15.07.2022
Elsevier BV |
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | •Efficient algorithm is needed for cracking Car-like Robot Path Planning problems.•An Improved Multi-objective PSO algorithm is proposed and compared with MOSPEA2.•Five objective functions are considered in solving multi-objective CRPP problems.•Totally six experiments were conducted to validate the proposed strategy.•Moving obstacles around the robot and a dynamic goal point were considered.
This paper introduces a method for car-like mobile robot path planning (CRPP). The robot works in both dynamic and static situations. The aim of this method is to explore the best safe path with minimum path length, minimum motor torque, minimum travel time, minimum robot acceleration and maximum obstacle avoidance. Kinodynamic and non-holonomic constraints related with car-like robot are considered. Fuzzy enhanced Improved Multi-objective Particle Swarm Optimization (FIMOPSO) algorithm is proposed to solve the CRPP problem. Fuzzy inference system is used for obstacle avoidance. In the proposed FIMOPSO, five improvements are made. Proposed technique is compared with Multi-objective Strength Pareto Evolutionary Algorithm 2 (MOSPEA2) technique. Experiments on a custom-made car-like robot are ensuring the quality of proposed technique. This research works show that proposed FIMOPSO is another alternative technique to CRPP problems. Paths dictated by FIMOPSO are safe, collision free, feasible, and possible and can be practically implemented. Fuzzy inference system works well for safe robot travel. FIMOPSO simulation paths are acceptable. Since, the deviation between experiment and simulation is less than 2%. |
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| AbstractList | This paper introduces a method for car-like mobile robot path planning (CRPP). The robot works in both dynamic and static situations. The aim of this method is to explore the best safe path with minimum path length, minimum motor torque, minimum travel time, minimum robot acceleration and maximum obstacle avoidance. Kinodynamic and non-holonomic constraints related with car-like robot are considered. Fuzzy enhanced Improved Multi-objective Particle Swarm Optimization (FIMOPSO) algorithm is proposed to solve the CRPP problem. Fuzzy inference system is used for obstacle avoidance. In the proposed FIMOPSO, five improvements are made. Proposed technique is compared with Multi-objective Strength Pareto Evolutionary Algorithm 2 (MOSPEA2) technique. Experiments on a custom-made car-like robot are ensuring the quality of proposed technique. This research works show that proposed FIMOPSO is another alternative technique to CRPP problems. Paths dictated by FIMOPSO are safe, collision free, feasible, and possible and can be practically implemented. Fuzzy inference system works well for safe robot travel. FIMOPSO simulation paths are acceptable. Since, the deviation between experiment and simulation is less than 2%. •Efficient algorithm is needed for cracking Car-like Robot Path Planning problems.•An Improved Multi-objective PSO algorithm is proposed and compared with MOSPEA2.•Five objective functions are considered in solving multi-objective CRPP problems.•Totally six experiments were conducted to validate the proposed strategy.•Moving obstacles around the robot and a dynamic goal point were considered. This paper introduces a method for car-like mobile robot path planning (CRPP). The robot works in both dynamic and static situations. The aim of this method is to explore the best safe path with minimum path length, minimum motor torque, minimum travel time, minimum robot acceleration and maximum obstacle avoidance. Kinodynamic and non-holonomic constraints related with car-like robot are considered. Fuzzy enhanced Improved Multi-objective Particle Swarm Optimization (FIMOPSO) algorithm is proposed to solve the CRPP problem. Fuzzy inference system is used for obstacle avoidance. In the proposed FIMOPSO, five improvements are made. Proposed technique is compared with Multi-objective Strength Pareto Evolutionary Algorithm 2 (MOSPEA2) technique. Experiments on a custom-made car-like robot are ensuring the quality of proposed technique. This research works show that proposed FIMOPSO is another alternative technique to CRPP problems. Paths dictated by FIMOPSO are safe, collision free, feasible, and possible and can be practically implemented. Fuzzy inference system works well for safe robot travel. FIMOPSO simulation paths are acceptable. Since, the deviation between experiment and simulation is less than 2%. |
| ArticleNumber | 116875 |
| Author | Sathiya, V. Chinnadurai, M. Ramabalan, S. |
| Author_xml | – sequence: 1 givenname: V. surname: Sathiya fullname: Sathiya, V. email: sathiyav2105@gmail.com organization: Department of Electronics and Communication Engineering, E.G.S. Pillay Engineering College, Nagapattinam 611002, Tamil Nadu, India – sequence: 2 givenname: M. surname: Chinnadurai fullname: Chinnadurai, M. email: mchinna81@gmail.com organization: Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam 611002, Tamil Nadu, India – sequence: 3 givenname: S. surname: Ramabalan fullname: Ramabalan, S. email: cadsrb@gmail.com organization: Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam 611002, Tamil Nadu, India |
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| Cites_doi | 10.1016/j.asoc.2020.106796 10.1109/ACCESS.2018.2864188 10.1007/s00500-015-1825-z 10.1504/IJWMC.2018.097194 10.1007/s00500-012-0964-8 10.1016/j.eswa.2020.114541 10.1016/j.cie.2021.107230 10.1007/s12555-019-0009-5 10.1007/s12555-019-0396-z 10.1016/j.asoc.2020.106076 10.1016/j.asoc.2017.05.012 10.1007/s12652-020-02535-5 10.1016/j.compag.2019.01.016 10.1007/s00500-015-1991-z 10.1016/j.neucom.2017.12.015 10.1080/0952813X.2018.1549107 10.1016/j.eswa.2016.03.035 10.1016/j.compeleceng.2020.106688 10.1016/j.arcontrol.2020.10.001 10.1016/j.eswa.2018.01.050 10.1016/j.robot.2019.103320 |
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| Keywords | MOSPEA2 Car-like robot path planning Non-holonomic and kinodynamic constraints Static and dynamic environments FIMOPSO |
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| References | Hidalgo-Paniagua, Vega-Rodríguez, Ferruz (b0010) 2016; 58 Maoudj, Hentout (b0005) 2020; 97 Qian, Liu, Tian, Bao (b0090) 2020; 85 Ahmed, Deb (b0050) 2013; 17 Ah King, Deb, Rughooputh (b0020) 2010; 16 Abwahab, Nefti-Meziani, Atyabi (b0105) 2020; 50 Hidalgo-Paniagua, Vega-Rodríguez, Ferruz, Pavón (b0015) 2017; 21 Feiyi, Haolun, Chi-Man, Haidong, Yujie, Yurong, Hao (b0060) 2020; 88 Xue, Sun (b0140) 2018; 8 Mac, Copot, Tran, De Keyser (b0125) 2017; 59 Wang, Li, Meng (b0080) 2021; 170 Zitzler, Laumanns, Thiele (b0145) 2001 Xia, Zhang, Weng, Liu, Wang (b0095) 2018; 35 Salmanpour, Monfared, Omranpour (b0120) 2017; 21 Moradi (b0030) 2019; 31 Velagić, Vuković, Ibrahimović (b0070) 2020; 18 Dao, Pan, Pan (b0130) 2016 Zhang, Zhang, Zhou (b0075) 2018; 6 Yunqiang, Wende, Lin, Xiaokun (b0065) 2018; 15 Miao, Chen, Yan, Yuanyuan (b0035) 2021; 156 Mohanty (b0100) 2020; 11 Ajeil, Ibraheem, Sahib, Humaidi (b0045) 2020; 89 Wang, Li, Guo, Chen (b0025) 2018; 282 Saeed, Recupero, Remagnino (b0115) 2020; 123 Mahmud, Abidin, Mohamed, Rahman, Iida (b0110) 2019; 157 Bayat, Najafi-Nia, Aliyari (b0055) 2018; 100 Durillo, Jośe Garćıa-Nieto, Nebro, Coello, Coello, Alba (b0085) 2009 Eberhart, Kennedy (b0040) 1995 Liu, Jiang (b0135) 2020; 18 Miao (10.1016/j.eswa.2022.116875_b0035) 2021; 156 Salmanpour (10.1016/j.eswa.2022.116875_b0120) 2017; 21 Eberhart (10.1016/j.eswa.2022.116875_b0040) 1995 Mahmud (10.1016/j.eswa.2022.116875_b0110) 2019; 157 Zitzler (10.1016/j.eswa.2022.116875_b0145) 2001 Hidalgo-Paniagua (10.1016/j.eswa.2022.116875_b0015) 2017; 21 Bayat (10.1016/j.eswa.2022.116875_b0055) 2018; 100 Mohanty (10.1016/j.eswa.2022.116875_b0100) 2020; 11 Abwahab (10.1016/j.eswa.2022.116875_b0105) 2020; 50 Yunqiang (10.1016/j.eswa.2022.116875_b0065) 2018; 15 Xue (10.1016/j.eswa.2022.116875_b0140) 2018; 8 Ah King (10.1016/j.eswa.2022.116875_b0020) 2010; 16 Maoudj (10.1016/j.eswa.2022.116875_b0005) 2020; 97 Moradi (10.1016/j.eswa.2022.116875_b0030) 2019; 31 Qian (10.1016/j.eswa.2022.116875_b0090) 2020; 85 Zhang (10.1016/j.eswa.2022.116875_b0075) 2018; 6 Liu (10.1016/j.eswa.2022.116875_b0135) 2020; 18 Velagić (10.1016/j.eswa.2022.116875_b0070) 2020; 18 Hidalgo-Paniagua (10.1016/j.eswa.2022.116875_b0010) 2016; 58 Ahmed (10.1016/j.eswa.2022.116875_b0050) 2013; 17 Wang (10.1016/j.eswa.2022.116875_b0080) 2021; 170 Saeed (10.1016/j.eswa.2022.116875_b0115) 2020; 123 Wang (10.1016/j.eswa.2022.116875_b0025) 2018; 282 Dao (10.1016/j.eswa.2022.116875_b0130) 2016 Durillo (10.1016/j.eswa.2022.116875_b0085) 2009 Xia (10.1016/j.eswa.2022.116875_b0095) 2018; 35 Feiyi (10.1016/j.eswa.2022.116875_b0060) 2020; 88 Ajeil (10.1016/j.eswa.2022.116875_b0045) 2020; 89 Mac (10.1016/j.eswa.2022.116875_b0125) 2017; 59 |
| References_xml | – volume: 89 year: 2020 ident: b0045 article-title: Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm publication-title: Applied Soft Computing – volume: 123 year: 2020 ident: b0115 article-title: A boundary node method for path planning of mobile robots publication-title: Robotics and Autonomous Systems – volume: 170 year: 2021 ident: b0080 article-title: Kinematic constrained bi-directional RRT with efficient branch pruning for robot path planning publication-title: Expert System with Applications – volume: 58 start-page: 20 year: 2016 end-page: 35 ident: b0010 article-title: Applying the MOVNS (multi-objective variable neighborhood search) algorithm to solve the path planning problem in mobile robotics publication-title: Expert Systems with Applications – volume: 16 start-page: 1 year: 2010 end-page: 27 ident: b0020 article-title: Comparison of NSGA-II and SPEA2 on the multiobjective environmental/economic dispatch problem publication-title: University of Mauritius Research Journal – start-page: 495 year: 2009 end-page: 509 ident: b0085 article-title: Multi-objective particle swarm optimizers: an experimental comparison publication-title: Proceedings of International Conference on Evolutionary Multi-criterion optimization. April 7 - 10, Nantes, France – volume: 97 year: 2020 ident: b0005 article-title: Optimal path planning approach based on q-learning algorithm for mobile robots publication-title: Applied Soft Computing – volume: 50 start-page: 233 year: 2020 end-page: 252 ident: b0105 article-title: A comparative review on mobile robot path planning: Classical or meta-heuristic methods? publication-title: Annual Reviews in Control – volume: 21 start-page: 3063 year: 2017 end-page: 3079 ident: b0120 article-title: Solving robot path planning problem by using a new elitist multi-objective IWD algorithm based on coefficient of variation publication-title: Soft Computing – volume: 17 start-page: 1283 year: 2013 end-page: 1299 ident: b0050 article-title: Multi-objective optimal path planning using elitist non-dominated sorting genetic algorithms publication-title: Soft Computing – volume: 282 start-page: 42 year: 2018 end-page: 51 ident: b0025 article-title: Car-like mobile robot path planning in rough terrain using multi-objective particle swarm optimization algorithm publication-title: Neurocomputing – volume: 85 year: 2020 ident: b0090 article-title: Robot path planning optimization method based on heuristic multi-directional rapidly-exploring tree publication-title: Computers & Electrical Engineering – volume: 6 start-page: 44542 year: 2018 end-page: 44555 ident: b0075 article-title: Path planning of mobile robot based on hybrid multi-objective bare bones particle swarm optimization with differential evolution publication-title: IEEE Access – volume: 11 start-page: 6387 year: 2020 end-page: 6402 ident: b0100 article-title: An intelligent navigational strategy for mobile robots in uncertain environments using smart cuckoo search algorithm publication-title: Journal of Ambient Intelligence and Humanized Computing – start-page: 337 year: 2016 end-page: 342 ident: b0130 article-title: A multi-objective optimal mobile robot path planning based on whale optimization algorithm publication-title: IEEE 13th international conference on signal processing (ICSP2016). IEEE – volume: 18 start-page: 1264 year: 2020 end-page: 1276 ident: b0070 article-title: Mobile robot motion framework based on enhanced robust panel method publication-title: International Journal of ControlAutom. Syst. – volume: 88 year: 2020 ident: b0060 article-title: A new global best guided artificial bee colony algorithm with application in robot path planning publication-title: Applied Soft Computing – volume: 8 start-page: 1 year: 2018 end-page: 21 ident: b0140 article-title: Solving the path planning problem in mobile robotics with the multi-objective evolutionary algorithm publication-title: Applied Sciences – volume: 31 start-page: 325 year: 2019 end-page: 348 ident: b0030 article-title: Multi-objective mobile robot path planning problem through learnable evolution model publication-title: Journal of Experimental and Theoretical Artificial Intelligence – volume: 157 start-page: 488 year: 2019 end-page: 499 ident: b0110 article-title: Multi-objective path planner for an agricultural mobile robot in a virtual greenhouse environment publication-title: Computers and Electronics in Agriculture – volume: 35 start-page: 1755 year: 2018 end-page: 1764 ident: b0095 article-title: Robot path planning based on multi-objective optimization with local search publication-title: Journal of Intelligent & Fuzzy Systems – volume: 156 year: 2021 ident: b0035 article-title: Path planning optimization of indoor mobile robot based on adaptive ant colony algorithm publication-title: Computers & Industrial Engineering – volume: 100 start-page: 68 year: 2018 end-page: 78 ident: b0055 article-title: Mobile robots path planning: electrostatic potential field approach publication-title: Expert Systems with Applications – volume: 59 start-page: 68 year: 2017 end-page: 76 ident: b0125 article-title: A hierarchical global path planning approach for mobile robots based on multi-objective particle swarm optimization publication-title: Applied Soft Computing – year: 2001 ident: b0145 article-title: SPEA2: Improving the strength pareto evolutionary algorithm publication-title: TIK Report 103, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Zurich, Switzerland – volume: 18 start-page: 2658 year: 2020 end-page: 2666 ident: b0135 article-title: Robotic path planning based on a triangular mesh map publication-title: International Journal of Control, Automation & System – volume: 21 start-page: 949 year: 2017 end-page: 964 ident: b0015 article-title: Solving the multi-objective path planning problem in mobile robotics with a firefly-based approach publication-title: Soft Computing – volume: 15 start-page: 335 year: 2018 end-page: 341 ident: b0065 article-title: Research on multi-objective path planning of a robot based on artificial potential field method publication-title: International Journal of Wireless and Mobile Computing – start-page: 39 year: 1995 end-page: 43 ident: b0040 publication-title: A new optimizer using particle swarm theory – volume: 88 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0060 article-title: A new global best guided artificial bee colony algorithm with application in robot path planning publication-title: Applied Soft Computing – volume: 97 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0005 article-title: Optimal path planning approach based on q-learning algorithm for mobile robots publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2020.106796 – volume: 6 start-page: 44542 year: 2018 ident: 10.1016/j.eswa.2022.116875_b0075 article-title: Path planning of mobile robot based on hybrid multi-objective bare bones particle swarm optimization with differential evolution publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2864188 – volume: 21 start-page: 949 year: 2017 ident: 10.1016/j.eswa.2022.116875_b0015 article-title: Solving the multi-objective path planning problem in mobile robotics with a firefly-based approach publication-title: Soft Computing doi: 10.1007/s00500-015-1825-z – volume: 15 start-page: 335 issue: 4 year: 2018 ident: 10.1016/j.eswa.2022.116875_b0065 article-title: Research on multi-objective path planning of a robot based on artificial potential field method publication-title: International Journal of Wireless and Mobile Computing doi: 10.1504/IJWMC.2018.097194 – start-page: 495 year: 2009 ident: 10.1016/j.eswa.2022.116875_b0085 article-title: Multi-objective particle swarm optimizers: an experimental comparison – start-page: 337 year: 2016 ident: 10.1016/j.eswa.2022.116875_b0130 article-title: A multi-objective optimal mobile robot path planning based on whale optimization algorithm – volume: 17 start-page: 1283 year: 2013 ident: 10.1016/j.eswa.2022.116875_b0050 article-title: Multi-objective optimal path planning using elitist non-dominated sorting genetic algorithms publication-title: Soft Computing doi: 10.1007/s00500-012-0964-8 – volume: 170 year: 2021 ident: 10.1016/j.eswa.2022.116875_b0080 article-title: Kinematic constrained bi-directional RRT with efficient branch pruning for robot path planning publication-title: Expert System with Applications doi: 10.1016/j.eswa.2020.114541 – volume: 156 year: 2021 ident: 10.1016/j.eswa.2022.116875_b0035 article-title: Path planning optimization of indoor mobile robot based on adaptive ant colony algorithm publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2021.107230 – volume: 18 start-page: 1264 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0070 article-title: Mobile robot motion framework based on enhanced robust panel method publication-title: International Journal of ControlAutom. Syst. doi: 10.1007/s12555-019-0009-5 – volume: 18 start-page: 2658 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0135 article-title: Robotic path planning based on a triangular mesh map publication-title: International Journal of Control, Automation & System doi: 10.1007/s12555-019-0396-z – volume: 89 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0045 article-title: Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2020.106076 – start-page: 39 year: 1995 ident: 10.1016/j.eswa.2022.116875_b0040 – volume: 59 start-page: 68 year: 2017 ident: 10.1016/j.eswa.2022.116875_b0125 article-title: A hierarchical global path planning approach for mobile robots based on multi-objective particle swarm optimization publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2017.05.012 – volume: 11 start-page: 6387 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0100 article-title: An intelligent navigational strategy for mobile robots in uncertain environments using smart cuckoo search algorithm publication-title: Journal of Ambient Intelligence and Humanized Computing doi: 10.1007/s12652-020-02535-5 – volume: 157 start-page: 488 year: 2019 ident: 10.1016/j.eswa.2022.116875_b0110 article-title: Multi-objective path planner for an agricultural mobile robot in a virtual greenhouse environment publication-title: Computers and Electronics in Agriculture doi: 10.1016/j.compag.2019.01.016 – volume: 8 start-page: 1 year: 2018 ident: 10.1016/j.eswa.2022.116875_b0140 article-title: Solving the path planning problem in mobile robotics with the multi-objective evolutionary algorithm publication-title: Applied Sciences – volume: 21 start-page: 3063 year: 2017 ident: 10.1016/j.eswa.2022.116875_b0120 article-title: Solving robot path planning problem by using a new elitist multi-objective IWD algorithm based on coefficient of variation publication-title: Soft Computing doi: 10.1007/s00500-015-1991-z – volume: 282 start-page: 42 year: 2018 ident: 10.1016/j.eswa.2022.116875_b0025 article-title: Car-like mobile robot path planning in rough terrain using multi-objective particle swarm optimization algorithm publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.12.015 – volume: 35 start-page: 1755 issue: 2 year: 2018 ident: 10.1016/j.eswa.2022.116875_b0095 article-title: Robot path planning based on multi-objective optimization with local search publication-title: Journal of Intelligent & Fuzzy Systems – volume: 31 start-page: 325 issue: 2 year: 2019 ident: 10.1016/j.eswa.2022.116875_b0030 article-title: Multi-objective mobile robot path planning problem through learnable evolution model publication-title: Journal of Experimental and Theoretical Artificial Intelligence doi: 10.1080/0952813X.2018.1549107 – volume: 58 start-page: 20 year: 2016 ident: 10.1016/j.eswa.2022.116875_b0010 article-title: Applying the MOVNS (multi-objective variable neighborhood search) algorithm to solve the path planning problem in mobile robotics publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2016.03.035 – volume: 85 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0090 article-title: Robot path planning optimization method based on heuristic multi-directional rapidly-exploring tree publication-title: Computers & Electrical Engineering doi: 10.1016/j.compeleceng.2020.106688 – volume: 50 start-page: 233 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0105 article-title: A comparative review on mobile robot path planning: Classical or meta-heuristic methods? publication-title: Annual Reviews in Control doi: 10.1016/j.arcontrol.2020.10.001 – volume: 100 start-page: 68 year: 2018 ident: 10.1016/j.eswa.2022.116875_b0055 article-title: Mobile robots path planning: electrostatic potential field approach publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2018.01.050 – volume: 16 start-page: 1 year: 2010 ident: 10.1016/j.eswa.2022.116875_b0020 article-title: Comparison of NSGA-II and SPEA2 on the multiobjective environmental/economic dispatch problem publication-title: University of Mauritius Research Journal – year: 2001 ident: 10.1016/j.eswa.2022.116875_b0145 article-title: SPEA2: Improving the strength pareto evolutionary algorithm – volume: 123 year: 2020 ident: 10.1016/j.eswa.2022.116875_b0115 article-title: A boundary node method for path planning of mobile robots publication-title: Robotics and Autonomous Systems doi: 10.1016/j.robot.2019.103320 |
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| Snippet | •Efficient algorithm is needed for cracking Car-like Robot Path Planning problems.•An Improved Multi-objective PSO algorithm is proposed and compared with... This paper introduces a method for car-like mobile robot path planning (CRPP). The robot works in both dynamic and static situations. The aim of this method is... |
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| SubjectTerms | Car-like robot path planning Collision avoidance Evolutionary algorithms FIMOPSO Inference MOSPEA2 Multiple objective analysis Non-holonomic and kinodynamic constraints Obstacle avoidance Particle swarm optimization Path planning Robots Static and dynamic environments Travel time |
| Title | Mobile robot path planning using fuzzy enhanced improved Multi-Objective particle swarm optimization (FIMOPSO) |
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