LAUSR

Abstract Haptic systems in surgical training applications require highly accurate force feedback. However, high-resolution models of the virtual environment (VE) can be very computationally intensive, lowering the force feedback update rate. The objective of this work is to improve transparency by developing a predictor that approximates the complex nonlinear VE as a linear VE with a much higher update rate. By using feedback from the more accurate but slower VE, the predictor can provide increased transparency to the operator. The full control design of the predictor and haptic controller is considered for a nonlinear haptic device. The predictor is designed using Lyapunov-based methods, by numerical solution of a linear matrix inequality. The predictor uses a projection-type adaptation law to estimate the unknown VE parameters. Simulation results are shown to demonstrate the effectiveness of the method assuming unknown and time-varying VE parameters.