Hybrid IDM/Impedance learning in human movements
Etienne Burdet, Chew Yin Teng, Bt · TUbilio (Technical University of Darmstadt) · 2001
In spite of motor output variability and the delay in the sensori-motor, humans routinely perform intrinsically un-stable tasks. The hybrid IDM/impedance learning con-troller presented in this paper enables skilful performance in strong stable and unstable environments. It consid-ers motor output variability identied from experimen-tal data, and contains two modules concurrently learning the endpoint force and impedance adapted to the envi-ronment. The simulations suggest how humans learn to skillfully perform intrinsically unstable tasks. Testable predictions are proposed. 1