An intelligent support system for teaching three or more degrees-of-freedom robotic manipulator

In this paper, we propose a smart teaching system for many complex tasks achieved by a seven degrees-of-freedom robotic manipulator. In this system, we basically use a sliced 2-D configuration plane because of no occlusion. In general, an enormous number of such planes exist in seven dimensional configuration space. To select some fruitful planes from all the planes, we develop a human support system based on efficient path finding and obstacle evaluating algorithms in each 2-D plane. The efficiency of this human computer cooperation system is compared with that of the model-based path-planning algorithm A*. Selecting a near-optimal path in our system is absolutely faster than calculating its optimal path by A*. This means that a human ability understanding a task is quite powerful especially for a seven-degrees-of-freedom robotic manipulator.