Genetic Algorithm-Based Optimization of the Rolling-Contact Involute Robot Joints

The hand exoskeleton has been widely studied in the fields of hand rehabilitation and grasping assistance tasks. Current hand exoskeletons face challenges in combining a user-friendly design with a lightweight structure and accurate modeling of hand motion. In our previous research work, we proposed a pure rolling involute biomimetic joint for the design of hand exoskeletons, resulting in a portable structure with high biomimetic performance. However, in the optimization of the biomimetic joint, the optimization algorithm for the joint surface was not intelligent enough, and several key parameters were manually adjusted, leading to suboptimal parameters obtained from the optimization process. Therefore, in this paper, we propose using genetic algorithms to optimize the parameters of the joint surface, aiming to achieve a joint with higher motion biomimetic performance. The optimization method presented in this paper not only improves the optimization effectiveness of the biomimetic joint but also provides new insights into multi-parameter optimization for other biomimetic joints.