Multi-Finger Collaborative Grasping Control for Prosthetic Hands Using Proximity Sensors

Traditional prosthetic hand grasping often relies on pre-programmed trajectories due to the lack of non-contact perception, leading to asynchronous finger contact, object displacement, and instability. To achieve synchronous multi-finger contact and adaptive pre-shaping, this paper presents a hierarchical control strategy driven by fingertip proximity sensing. We integrate miniature reflective light-intensity sensors on each fingertip for real-time distance measurement. The core innovations include: A master-slave phase compensation architecture featuring dynamic master finger election to coordinate finger movements towards an equidistant plane relative to the target object; Lyapunov stability-based anti-disturbance allocation to dynamically redistribute control effort among fingers when disturbances occur, maintaining grasp envelope stability. Implemented solely on an embedded microcontroller, the system requires no complex external computation or electromyographic signals. Experimental validation on a 5-DOF prosthetic hand demonstrates successful adaptive pre-shaping for various objects. Results show high positional accuracy, significantly improved grasp success rate, minimal multi-finger synchronization error, and robust disturbance rejection. This approach significantly enhances the continuity, stability, and environmental adaptability of prosthetic grasping in unstructured settings.