期刊
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
卷 79, 期 2, 页码 237-257出版社
SPRINGER
DOI: 10.1007/s10846-014-0124-8
关键词
Mobile robot navigation; Path planning; Artificial potential field; APF; PEAPF; Parallel evolutionary computation
资金
- Instituto Politecnico Nacional (IPN)
- Comision de Fomento y Apoyo Academico del IPN (COFAA), an the Mexican National Council of Science and Technology (CONACYT)
In this paper, we introduce the concept of Parallel Evolutionary Artificial Potential Field (PEAPF) as a new method for path planning in mobile robot navigation. The main contribution of this proposal is that it makes possible controllability in complex real-world sceneries with dynamic obstacles if a reachable configuration set exists. The PEAPF outperforms the Evolutionary Artificial Potential Field (EAPF) proposal, which can also obtain optimal solutions but its processing times might be prohibitive in complex real-world situations. Contrary to the original Artificial Potential Field (APF) method, which cannot guarantee controllability in dynamic environments, this innovative proposal integrates the original APF, evolutionary computation and parallel computation for taking advantages of novel processors architectures, to obtain a flexible path planning navigation method that takes all the advantages of using the APF and the EAPF, strongly reducing their disadvantages. We show comparative experiments of the PEAPF against the APF and the EAPF original methods. The results demonstrate that this proposal overcomes both methods of implementation; making the PEAPF suitable to be used in real-time applications.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据