A Data-Observation Hybrid Compensation Method for Precise Force Control of Cable-Driven Wrist Exoskeletons in Teleoperation

High-precision force control of wearable exoskeletons enables highly transparent force interaction operations, effectively improving the feasibility of teleoperation tasks. We adopted a cable-driven spherical parallel wrist exoskeleton (SPWE) which enables it to reduce the volume and enhance operational flexibility; however, significant hysteresis effects and nonlinear friction lead to insufficient force control accuracy. This paper proposes a Data-Observation Hybrid Compensation (DOHC) method, which constructs a Gaussian process-based hysteresis-aware model using physical characteristics. With critical velocity as the judgment criterion, a friction observer is introduced under quasi-static conditions to achieve high-precision compensation across both quasi-static and motion states. Experimental results demonstrate that DOHC significantly improves friction modeling accuracy and joint torque tracking performance in SPWE, and exhibits effective force transparency in haptic rendering experiments, providing reliable technical support for immersive teleoperation tasks.