Designing robots for optimal performance during repetitive motion

As robots assume more important roles in flexible manufacturing environments, they are expected to perform repeated motions while being able to quickly adapt to changes in the assembly line. It can not be ignored that the parameters of the robot influence the cost per cycle. This cost gets multiplied by the number of cycles to result in the operational cost over time. However, today, no attempts are made to design robots so that their parameters could be adjusted to the optimal values for a repeated sequence of motion. We propose a technique to identify the optimal parameters of a robot for a motion sequence between two given states in a prescribed time such that a cost functional is minimized. This proposed technique of solving this problem is new and does not use Lagrange multipliers. It is computationally efficient and the optimal parameters can be identified quickly. As a result, the parameters of a robot could be altered online in the execution of new sequences of motion.