Multi-Agent System-Based Fuzzy Controller Design with Genetic Tuning for a Mobile Manipulator Robot in the Hand Over Task

This paper presents an application of the multi-agent system approach to a service mobile manipulator robot that interacts with a human during an object delivery and hand-over task in two dimensions. The base, elbow and shoulder of the robot are identified as three different agents, and are controlled using fuzzy control. The control variables of the controllers are linear velocity of the base, angular velocity of the elbow, and angular velocity of the shoulder. Main inputs to the system are the horizontal and vertical distances between the human and robot hands. These are input to all three agents. In developing the fuzzy control rules, effective delivery and avoidance of contact with humans, not to cause physical damage, are considered. The membership functions of the fuzzy controllers are tuned by using genetic algorithms. In tuning, the performance is calculated considering the distance deviation from the direct path, time spent to reach the human hand and energy consumed by the actuators. The proposed multi-agent system structure based on fuzzy control for the object delivery task succeeded in both effective and safe delivery.