Designing robots for optimal performance during repetitive motion

It is quite common to see robots on assembly lines perform the same motion every sequence for long periods of time. Periodically, the robots are reprogrammed to carry out a new sequence. It can not be ignored that the parameters of the robot influence the cost per cycle. This cost is multiplied by the number of cycles to result in the operational cost over a period of time. However, today, no attempts are made to design robots so that their parameters could be adjusted to the optimal values for a given sequence of motion. In this paper, 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. The proposed technique of solving this problem is new and does not use Lagrangian multiplier. It is highly computation efficient and the optimal parameters can be obtained within seconds. As a result, the parameters of a robot could be altered online as it is programmed to execute a new repetitive task