在移动机器人的路径规划中应用改进的Sparrow搜索算法
Yong Xu1, Bicong Sang1, Yi Zhang1
1College of Electrical and Computer Science, Jilin Jianzhu University, Changchun 130119, China.
Biomimetics (Basel, Switzerland)
|June 26, 2024
概括
改进的搜索算法 (ISSA) 提高了移动机器人路径规划的效率和稳定性. 这种算法提供了优越的路径长度,减少了运行时间,与标准方法相比,提供了更好的最佳性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 优化算法 优化算法
背景情况:
- 有效,稳定和安全的路径规划对于现代机器人技术至关重要.
- 现有的算法在复杂和动态的环境中面临着挑战.
研究的目的:
- 引入一个改进的乌搜索算法 (ISSA) 来改进路径规划.
- 为了提高移动机器人路径规划的效率,稳定性和最佳性.
主要方法:
- 使用循环混乱映射对人口多样性的初始化.
- 纳入北戈肖克的位置更新以进行更广泛的搜索.
- 莱维飞行战略,以提高全球优化.
- 适应性T分布突变,以提高本地勘探和收速度.
主要成果:
- 在标准的子搜索算法 (SSA) 上,ISSA表现出优越的性能.
- 在路径长度,运行时间,路径最佳性和稳定性方面注意到了改进.
- 对CEC2021功能集和移动机器人路径规划场景的验证.
结论:
- 拟议的ISSA对移动机器人路径规划是有效的,稳健的和可行的.
- 对于复杂的路径规划任务,ISSA比现有方法具有显著的优势.
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