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An iterative algorithm to minimize energy loss in kinematic chains is proposed. This algorithm is designed to low level of control where variables such as terminal states, runtime, and physical and electrical parameters of the movement are given by higher levels of control. An original complex problem of optimization is transformed into a simple quadratic programming problem subject to linear constraints by discretizing all dynamic system variables. The whole system is then converted into a recursive matrix equation that is solved iteratively. A proof of convergence is suggested. The performance of the algorithm is illustrated by using it in the motion planning of a quadruped robot.
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