Innovative Design of Multi-Functional Supernumerary Robotic Limbs with Ellipsoid Workspace Optimization
Jun Huo, Jian Huang, Jie Zuo, Bo Yang, Zhongzheng Fu, Xi Li, Samer Mohammed
Abstract
Supernumerary robotic limbs (SRL) offer substantial potential in both the rehabilitation of hemiplegic patients and the enhancement of functional capabilities for healthy individuals. Designing a general-purpose SRL device is inherently challenging, particularly when developing a unified theoretical framework that meets the diverse functional requirements of both upper and lower limbs. In this paper, we propose a MOO design theory that integrates grasping workspace similarity, walking workspace similarity, bracing force for STS movements, and overall mass and inertia. To facilitate rapid and stable convergence of the model to high-dimensional irregular Pareto fronts, we introduce a multi-subpopulation correction firefly algorithm. The optimized solution is utilized to redesign the prototype for experimentation to meet specified requirements. Six healthy participants and two hemiplegia patients participated in real experiments. Compared to the pre-optimization results, the average grasp success rate improved by 7.2%, while muscle activity during walking and STS tasks decreased by an average of 12.7% and 25.1%, respectively, following the optimization.