Abstract
The development and validation of a sensor-driven control model for multijointed cooperating robotic arms is explored. The approach is used to explore an anthropomorphic model, and to then reason by analogy to discover a robust control model for robotic arm motion. This approach uses human-like joint motion profiles and sensory information of all joints, evaluates the weighted work done by each joint in cooperative motion, and then synthesizes a minimal effort motion trajectory to precisely and efficiently position the robotic arm end effector. This sensor-based approach significantly reduces the computational requirements for such cooperative motion. The result is a less complex, faster, and adaptive control process. A pressure-servoed hydraulic motion system has been developed to implement the movement strategy. This is a major step toward a long-term research goal of conceptualizing in an intelligent way to implement a manufacturing task.<>