Distributed control of simulated autonomous mobile robot collectives in payload transportation

A behavior-based control paradigm that allows a distributed collection of autonomous mobile robots to control the lifting and lowering processes of payload transportation is proposed and then tested with computer simulations. This control paradigm, which represents an approach to solving the cooperative load-bearing problem inherent in multi-agent payload transportation, is based upon a control structure we term thebehavior pathway controller. The behavior pathway controller emphasizes simple, feasible methodologies over complex, optimal methodologies, although we show that with some global self-organization of the collective, the feasible solutions approach and become optimal solutions. Using this controller in simulated environments, our robots demonstrate an ability to function with inaccurate sensor data, which is an important consideration for real world implementations of an autonomous mobile robot control paradigm. The simulated robots also demonstrate an ability to learn their place, or role, within the collective. They must learn their relative roles because they possess no predetermined knowledge about pallet mass, pallet inertia, collective size, or their positions relative to the pallet's center of gravity.