On the Influence of Hand Dynamics on Motion Planning of Reaching Movements in Haptic Environments

The paper presents an analysis of human reaching movements in the manipulation of flexible objects. Two models, the minimum hand jerk and the minimum driving hand forcechange, are used for modelling and verification of experimental data. The data are collected with the haptic system supporting dynamic simulation of the flexible object in real time. We describe some initial experimental results and analyze the applicability of the models. It is found that even for short-term movements human motion planning strategy can depend on arm inertia and configuration. This conclusion is based on the experimental evidence of the multi-phased hand velocity profiles that can be well captured by the minimum driving hand force-change criterion. To support the latest observation, an experiment with reinforcement learning was conducted.