A minimum effort control algorithm for a cooperating sensor driven intelligent multi-jointed robotic arm

A minimum effort control algorithm for multijointed cooperating robotic arms is described. This algorithm generates several humanlike arm movement strategies and selects the best strategy on the basis of expendable effort. The algorithm has an inherent basis for dealing with obstacles in an efficient manner. The proposed approach involves: exploring the anthropomorphic model, and reasoning then by analogy to discover a robust control model for robotic arm motion; using humanlike joint motion profiles: using sensory information of all joints; evaluating the weighted work done by each joint in cooperative motion; and then synthesizing a minimal effort motion trajectory to precisely and efficiently position the robotic arm end effector. Parallel processing techniques are used in the present control model. This agrees with the observation that cooperating robotic motion has a significant degree of concurrency. The software approach is object-oriented and exploits this concurrency, resulting in a usable and expandable control model