Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning
In this paper two novel Particle Swarm Optimization (PSO)-based algorithms are presented for robot path planning with respect to two objectives, the shortest and smoothest path criteria. The first algorithm is a hybrid of the PSO and the Probabilistic Roadmap (PRM) methods, in which the PSO serves...
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| Format: | Article |
| Language: | English |
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Stefan cel Mare University of Suceava
2010-11-01
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| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2010.04011 |
| _version_ | 1818583306574233600 |
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| author | SEDIGHIZADEH, D. MASEHIAN, E. |
| author_facet | SEDIGHIZADEH, D. MASEHIAN, E. |
| author_sort | SEDIGHIZADEH, D. |
| collection | DOAJ |
| description | In this paper two novel Particle Swarm Optimization (PSO)-based algorithms are presented for robot path planning with respect to two objectives, the shortest and smoothest path criteria. The first algorithm is a hybrid of the PSO and the Probabilistic Roadmap (PRM) methods, in which the PSO serves as the global planner whereas the PRM performs the local planning task. The second algorithm is a combination of the New or Negative PSO (NPSO) and the PRM methods. Contrary to the basic PSO in which the best position of all particles up to the current iteration is used as a guide, the NPSO determines the most promising direction based on the negative of the worst particle position. The two objective functions are incorporated in the PSO equations, and the PSO and PRM are combined by adding good PSO particles as auxiliary nodes to the random nodes generated by the PRM. Both the PSO+PRM and NPSO+PRM algorithms are compared with the pure PRM method in path length and runtime. The results showed that the NPSO has a slight advantage over the PSO, and the generated paths are shorter and smoother than those of the PRM and are calculated in less time. |
| first_indexed | 2024-12-16T08:03:11Z |
| format | Article |
| id | doaj.art-b82f7a40a1734b0bb68d56bc55c071ad |
| institution | Directory Open Access Journal |
| issn | 1582-7445 1844-7600 |
| language | English |
| last_indexed | 2024-12-16T08:03:11Z |
| publishDate | 2010-11-01 |
| publisher | Stefan cel Mare University of Suceava |
| record_format | Article |
| series | Advances in Electrical and Computer Engineering |
| spelling | doaj.art-b82f7a40a1734b0bb68d56bc55c071ad2022-12-21T22:38:33ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002010-11-01104697610.4316/AECE.2010.04011Multi-Objective PSO- and NPSO-based Algorithms for Robot Path PlanningSEDIGHIZADEH, D.MASEHIAN, E.In this paper two novel Particle Swarm Optimization (PSO)-based algorithms are presented for robot path planning with respect to two objectives, the shortest and smoothest path criteria. The first algorithm is a hybrid of the PSO and the Probabilistic Roadmap (PRM) methods, in which the PSO serves as the global planner whereas the PRM performs the local planning task. The second algorithm is a combination of the New or Negative PSO (NPSO) and the PRM methods. Contrary to the basic PSO in which the best position of all particles up to the current iteration is used as a guide, the NPSO determines the most promising direction based on the negative of the worst particle position. The two objective functions are incorporated in the PSO equations, and the PSO and PRM are combined by adding good PSO particles as auxiliary nodes to the random nodes generated by the PRM. Both the PSO+PRM and NPSO+PRM algorithms are compared with the pure PRM method in path length and runtime. The results showed that the NPSO has a slight advantage over the PSO, and the generated paths are shorter and smoother than those of the PRM and are calculated in less time.http://dx.doi.org/10.4316/AECE.2010.04011swarm roboticinfraredAMiRmodulation methods |
| spellingShingle | SEDIGHIZADEH, D. MASEHIAN, E. Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning Advances in Electrical and Computer Engineering swarm robotic infrared AMiR modulation methods |
| title | Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning |
| title_full | Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning |
| title_fullStr | Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning |
| title_full_unstemmed | Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning |
| title_short | Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning |
| title_sort | multi objective pso and npso based algorithms for robot path planning |
| topic | swarm robotic infrared AMiR modulation methods |
| url | http://dx.doi.org/10.4316/AECE.2010.04011 |
| work_keys_str_mv | AT sedighizadehd multiobjectivepsoandnpsobasedalgorithmsforrobotpathplanning AT masehiane multiobjectivepsoandnpsobasedalgorithmsforrobotpathplanning |