摘要
针对机器人完成任务不均衡问题展开分析,提出了基于混合算法的规划算法,包括适应度值分类的K-means聚类实现任务分配、黏菌算法提高整体搜索效率、头脑风暴算法机器人内进行局部更新操作和机器人间进行全局更新操作完成重规划操作、交叉操作和大规模邻域搜索操作用以更新个体.实验结果表明:基于混合算法的任务均衡规划方法能够均衡规划多机器人任务,优化任务规划结果,提升任务的完成效率.
Based on the analysis of the problem of unbalanced tasks completed by robots,a planning algorithm based on hybrid algorithm is proposed.It includes fitness value classification of K-means clustering for task allocation,slime mold algorithm to improve the overall search efficiency,brainstorming algorithm for local update operation in robot and global update operation in robot for re-planning operation,crossover operation and large-scale neighborhood search operation to update individuals.The experimental results show that the task balancing planning method based on hybrid algorithm can balance multi-robot tasks,improve task planning results and improve task completion efficiency.
作者
王喜敏
袁杰
WANG Ximin;YUAN Jie(School of Electrical Engineering,Xinjiang University,Urumqi Xinjiang 830017,China)
出处
《新疆大学学报（自然科学版）（中英文）》
CAS
2023年第2期210-221,共12页
Journal of Xinjiang University(Natural Science Edition in Chinese and English)
基金
国家自然科学基金“非结构环境下机器人羽流寻源自主演进策略研究”(62263031),“机器人化单分子病毒可控侵染细胞及原位定量表征方法研究”(62073227)
新疆维吾尔自治区自然科学基金“非结构环境下机器人建图与主动安全方法研究”(2022D01C53)。
