基于K-means聚类算法的群体机器人聚集队形控制

Swarm Robots Aggregation Formation Control Based on K-means Clustering Algorithm

针对未知环境下的群体机器人形成聚集动态队形的问题进行研究,分析了群体机器人运动控制策略,将K-means聚类算法与复合机体结构队形控制策略相结合,确定群体机器人聚类中心;个体机器人根据局部感知自主产生队形控制行为矢量,奔向目标,躲避障碍物;产生四种行为控制参数,确定机器人运动速度大小及方向;聚集成为圆形并排列成为三角形队形。仿真实验表明了K-means聚类算法与复合机体结构控制策略相结合的可行性和有效性。

Unknown environment for groups of robots form gathering dynamics formation problem to stud- y, Analysis groups of robots motion control strategy, The K-means clustering algorithm combined with com- posite body structure formation control strategy, Groups of robots to determine the cluster center; Individual perception of self-produce robot formation according to local vector control activities, Toward the goal, A- void obstacles ;Produce four kinds of behavior control parameters ,Determine the size and direction of the robot velocity ,Gathered and arranged into a triangle formation round. Simulation results show that the K- means clustering algorithm combined with body structure control strategy feasibility and effectiveness