This chapter presents an analysis of human-like reaching movements in manipulation of parallel flexible objects. To predict a trajectory of the human hand, a minimum hand-jerk model and a minimum hand-force-change model based on the minimization of the integral of, respectively, squared hand jerk and squared time derivative of the hand force over the movement duration are established. It is shown that within these models, the optimal hand trajectory is composed of a fifth-order polynomial and trigonometric terms depending on the natural frequencies of the system and movement time. To estimate the mass of the hand featured in the minimum hand-force-change model, a method based on following a periodic force input is proposed. A virtual reality-based experimental setup with a haptic simulator is designed, and the predictions by the minimum hand-jerk and force-change models are verified against experimental data. The theoretical predictions match the collected data with a reasonable accuracy. The experimental results show the applicability of the two considered models for the generation of human-like reaching movements in dynamic environments.
|Title of host publication||Human Inspired Dexterity in Robotic Manipulation|
|Number of pages||23|
|Publication status||Published - Jun 29 2018|
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