Using supervisory control methods for model based control of multi-agent systems

The development of control systems for multiple cooperating robot manipulators with redundant kinematics is still a demanding task. This task becomes even more challenging if the robots to be controlled operate in at least partly unknown environments which vary over time and which may be thousands of kilometers away from the operator, for example in space. To solve this task, the Institute of Robotics Research (IRF) combines supervisory control methods in the form of the newly developed state oriented modeling methodology with latest robot simulation technology, realizing an absolutely new approach for robot control purposes. This approach regards the robots manipulators from a discrete event system point of view. Using the state oriented modeling methodology, supervisors and controllers for those systems can be developed in a nearly intuitive way resulting in robust, fault-tolerant robot controllers. Using 3D simulation technology for model based robot control, the robot controller knows not only its own kinematic chain but also all the objects in its environment. This simplifies the task of object oriented robot programming, sensor information processing, environment model update, etc. once more. On the other hand, this allows for a smooth transition from robot simulation to robot control, because the same algorithms simulate the virtual and control the physical robots.