RAR-6: An Optimized Reconfigurable Asymmetric 6-DOF Haptic Robot for Gross and Fine Motor Tasks

Robot-assisted task-oriented training demonstrates immense potential in rehabilitation area. Parallel robots, with advantages such as low inertia and high stiffness, facilitate precise haptic feedback, yet their application in rehabilitation is limited by workspace constraints. To this end, we propose a design scheme for a haptic robot based on a reconfigurable asymmetric parallel mechanism. We first introduce a two-stage multi-objective optimization method to obtain the optimal parameter configurations. Then, to achieve precise assembling of the reconfigurable mechanism in each configuration, corresponding positioning mechanisms are designed. System performance tests validate the robot's capabilities under different configurations: workspace meets design requirements, stiffness output reaches 30 N/mm, force output is 40 N, RMS of maximum back-driven force along $x, y$, and $z$ axes is 7.5 N, and RMS of maximum back-driven torque around $x$ and y axes is 567.4 N. mm. Target tracking and virtual channel trajectory tracking experiments demonstrate the system's haptic rendering ability for gross motor tasks (GMTs) and fine motor tasks (FMTs), respectively. The developed 6-DOF haptic robot holds promise for versatile task-oriented rehabilitation training.