@inproceedings{db34446b38144de8b40d145340598aa7,
title = "A comparative study of smooth path planning for a mobile robot by evolutionary multi-objective optimization",
abstract = "This paper studies the evolutionary planning strategies for mobile robots to move smoothly along efficient collision-free paths in known static environments. The cost of each candidate path is composed of the path length and a weighted sum of penetration depth to vertices of polygonal obstacles. The path is composed of a pre-specified number of cubic spiral segments with constrained curvature. Comparison of the path planning performance between two Pareto-optimal schemes, the parallel genetic algorithm scheme based on the island method (PGA) and the non-dominated sorting genetic algorithm (NSGA-II), are conducted in terms of success rate in separate runs and path length whenever collision-free paths are found. Numerical simulation results are presented for three types of obstacles: polygons, walls, and combinations of both.",
author = "Hung, {Kao Ting} and Liu, {Jing Sin} and Chang, {Yau Zen}",
year = "2007",
doi = "10.1109/CIRA.2007.382857",
language = "英语",
isbn = "1424407907",
series = "Proceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007",
pages = "254--259",
booktitle = "Proceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007",
note = "2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007 ; Conference date: 20-06-2007 Through 23-06-2007",
}