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Updated: Feb 28, 2026

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拓进步潜在增强的连续空间殖民地算法用于机器人路径规划

Guikun Dong1, Feixiong Zhao1, Jiaxiong Zhuo1

  • 1School of Mechanical Engineering, Chengdu University, Chengdu 610106, China.

Sensors (Basel, Switzerland)
|February 27, 2026
PubMed
概括

一个新的拓进步潜在增强的连续空间殖民地路径规划算法 (TPP-CSACO) 通过增强全球指导和避开障碍来改善路径规划. 与传统算法相比,这种方法可以实现更短的路径,更好的流性和更高的安全性.

关键词:
殖民地优化算法殖民地优化算法连续空间连续空间.弹性步骤大小 弹性步骤大小全球路径规划全球路径规划基于部门的感知.

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