南京航空航天大学学报2025，Vol.57Issue(3)：419-428,10.DOI:10.16356/j.1005-2615.2025.03.003
基于灰狼优化算法的模块化机器人拓扑优化方法
An Optimization Method for Modular Robot Topology Based on GWO
摘要
Abstract
The modular robot can be reconstructed into different topologies and can meet complex and changeable task requirements.How to find the optimal topology of a modular robot with specific working capabilities is the key to fully appropriate its reconfiguration characteristics.To solve this problem,this paper proposes a modular robot topology optimization method based on grey wolf optimizer(GWO).First,the kinematic chain representation is constructed for the modular robot,and the kinematic/dynamic modeling is completed based on the screw method and the Newton-Euler method.Second,the topology decision variables are designed based on the representation of the motion chain,and the objective function is designed considering the number of modules,the maximum joint driving torque and dexterity of the robot.The concepts of crossover and mutation are introduced to improve the GWO,and the topology optimization model is established and solved.Finally,the optimal topologies corresponding to two experiments are compared to verify that the algorithm can effectively solve the optimal topology of a modular robot.关键词
模块化机器人/拓扑表征/拓扑优化/灰狼优化算法/多目标优化Key words
modular robot/topological representation/optimal topology/grey wolf optimizer(GWO)/multi-objective optimization分类
计算机与自动化引用本文复制引用
刘玖庆,陈钢,费军廷,余龙畅,闫英,刘育强,刘华伟..基于灰狼优化算法的模块化机器人拓扑优化方法[J].南京航空航天大学学报,2025,57(3):419-428,10.基金项目
国家自然科学基金(62173044) （62173044）
北京邮电大学优秀博士生创新基金(CX20243079) （CX20243079）
北京邮电大学研究生创新创业项目(2025-YC-T034). （2025-YC-T034）
