This paper presents a multi-objective optimal design method for gravity compensators with consideration of minimizing the joint reaction forces. High performance of the gravity compensation is achieved while the joint reaction forces are kept to a minimum. In this method, the ratio of the compensated torque to the uncompensated torque and the maximum value of the joint reaction forces are formulated as cost functions in the optimization problem, which is solved by adopting the Pareto front of multiple fitness functions with a genetic algorithm. This work takes a spring four-bar mechanism as a gravity compensator for a case study. The theoretical models of a gravity compensator and a robot manipulator show that the proposed multi-objective optimal design allows for the achievement of smaller joint reaction forces than the original single-objective optimal design, while their gravity compensation performances are relatively the same. Moreover, a prototype of a 0.2-kg gravity compensator realized from the proposed method was also built. An experimental study with this prototype showed that the measured motor torque was reduced by up to 93% within a range of 3π/4.
Journal of Mechanisms and Robotics Open Issues
