The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Evolutionary artificial potential fields and their application in real time robot path planning
Abstract
A new methodology named Evolutionary Artificial Potential Field (EAPF) is proposed for real-time robot path planning. The artificial potential field method is combined with genetic algorithms, to derive optimal potential field functions. The proposed EAPF approach is capable of navigating robot(s) situated among moving obstacles. Potential field functions for obstacles and goal points are also defined. The potential field functions for obstacles contain tunable parameters. The multi-objective evolutionary algorithm (MOEA) is utilized to identify the optimal potential field functions. Fitness functions such as goal-factor, obstacle-factor, smoothness-factor and minimum-pathlength-factor are developed for the MOEA selection criteria. An algorithm named escape-force is introduced to avoid the local minima associated with EAPF. Moving obstacles and moving goal positions were considered to test the robust performance of the proposed methodology. Simulation results show that the proposed methodology is efficient and robust for robot path planning with non-stationary goals and obstacles.
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Citations
Cites
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Khatib, O. (1986) · The International Journal of Robotics Research · doi:10.1177/027836498600500106 · Cited by 7,894
Cited by
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Luong, N. C., Hoang, D. T., Gong, S., Niyato, D., Wang, P., Liang, Y.-C., & Kim, D. I. (2018) · arXiv · doi:10.48550/arxiv.1810.07862 · Cited by 17
Metadata
- Authors
- Vadakkepat, P., Tan, K. C., & Ming-Liang, W.
- Venue
- Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)
- Publisher
- IEEE
- Published
- 2002-11-07
- Volume
- 1
- Pages
- 256-263
- OpenAlex
- W1904799423
- Cited by
- 346
- References
- 1
- FWCI
- 4.02
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Vadakkepat, P., Tan, K. C., & Ming-Liang, W. (2002). Evolutionary artificial potential fields and their application in real time robot path planning. Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512). https://doi.org/10.1109/cec.2000.870304
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