An Affection-Based Dynamic Leader Selection Model for Formation Control in Multirobot Systems
提出一种基于情感的多机器人系统动态领导者选择模型，利用模糊推理评估机器人状态，当领导者羞愧值超过阈值时触发重新选择，并通过交换贪婪算法优化领导者-跟随者关系，提升团队逃离局部极值点的能力。
In this paper, a dynamic leader selection process of a multirobot system with leader-follower strategies is studied in terms of formation control. A fuzzy inference system is employed to evaluate the status of robots by means of their states. Based on the status, an affection-based model is proposed to trigger a leader selection module. Followers send out unsatisfied signals when they are disappointed at the current leader. The abashment value of the leader changes with its own status as well as the number of unsatisfied signals received from its followers. When its abashment value goes beyond a given threshold, a leader reselection process is triggered. Moreover, a swap-greedy algorithm is proposed to approximate the optimal solution for confirming the leader-follower relationship, which can be described as a combinatorial optimization problem to minimize the total travel distance of all the robots. Extensive simulation results demonstrate that the proposed model can improve the probability of a robot team escaping from local extreme points significantly, and even in the case of leader failure, the team can reselect a leader autonomously and keep moving toward the target.