Office delivery robot controlled by modular behavior selection networks with planning capability

Recently, assistance service using mobile robots becomes one of important issues. Accordingly, studies on controlling the mobile robots are spreading all over the world. In this line of research, we propose a hybrid architecture based on hierarchical planning of modular behavior selection networks for generating autonomous behaviors of the office delivery robot. Behavior selection network is suitable for goal-oriented problems, but it is too difficult to design a monolithic behavior network to deal with complex robot control. We decompose it into several smaller behavior modules and construct sequences of the modules considering the sub-goals, the priority in each task and the user feedback. The feasibility of the proposed method is verified on both the Webot simulator and Khepera II robot in an office environment with delivery tasks. Experimental results confirm that a robot can achieve goals and generatemodule sequences successfully even in unpredictable and changeable situations, and the proposed planning method reduces the elapsed time during tasks by 17.5%.