Topological Structure Learning Based Enclosing Formation Behavior for Monitoring System
Yuichiro Toda, Naoyuki Kubota · 2018
Recently, the expectation to teleoperated mobile robots has been increasing much in order to perform the monitoring in various scenes. However, there are many critical problems in the teleoperated mobile robots. In this paper, we discuss cooperative formation behavior of teleoperated multiple robots. Especially, we focus on an enclosing formation behavior of a target object. First, we define the problem setting of the enclosing formation behavior. In our method, the enclosing formation is divided by two strategies in order to reduce the search space of robot poses. Next, we introduce Batch Learning Growing Neural Gas (BL-GNG) in order to improve the learning convergence and reduce the user-designed parameters in GNG. BL-GNG uses an objective function based on Fuzzy C-means for improving the learning convergence. Furthermore, we apply two-layers BL-GNG to decide the positions of enclosing formation. Finally, we show several experimental results of the proposed method.