人間形ロボットハンドの高機能化に関する研究
—ハンド · アームの動作分類を用いた接触覚センサベース制御—

抄録

Demand for fine human function modeling methodology is rising with the popularization of assistive devices. Systems engineering based research that delves into the functional cooperative relationship of the digits, hand, and arm is needed for design of substitutive mechanisms and for their control of the human body. The optimal tool for such research is the design process of a sensor-based robotic hand-arm system. This paper discusses the research issues and our proposed strategy.
Our research goal is to develop a sensory-controlled mechanical system for performing versatile human-like prehension. As a design concept, we propose an effective model extracted from functional analysis of the upper limb. The key assumption in categorizing hand behavior is the arm’s driving function. Without proper integration of the two, the hand function can be neither analyzed nor assembled. Our approach uses this assumption as its base; we propose a method for classifying a non-redundant relation to control the dynamic and static use of the artificial upper limb.
We began remodeling the degrees of freedom (DOF) of the human hand by identifying the transverse and longitudinal adjustable arch structure in the hand. Our new model is composed of 21 active DOF, which include movement in the palm. We classified movements and postures of the hand and arm with this DOF model located at the end of a seven-DOF arm. We then classified the hand modes as prehensile forms and sustentacular forms.
Based on this model and our previous research experience in developing prosthetic upper limbs and anthropomorphic robotic hands, we devised a robotic hand-arm with a total of 24 degrees of freedom. Additionally, a new multitactile sensor has been developed for use on the robotic hands in our laboratory at TDU.
For generating control strategy, the behavior of the hand is classified into two divisions. The first is cooperation of the digits and palm, and the second is cooperation of the hand and arm modules. The digit cooperation task is fourfold: formation, transformation, deformation, and hold. A motion planner drives the digit movements from the relation of the hand forms to the task that is proposed.
A tactile sensor-based control strategy is presented. The digits are controlled according to the hand modes and the sensory feedback loop, with slippage detection rules. Two strategies are proposed for extending the control for fine manipulation: cooperative slippage sensing of adjacent digits, and slippage prediction applying hand orientation information measured by an inclinometer.
The overall objective of our approach is the design of a dexterous control system for a multi-DOF robotic upper limb. This includes discussion of a modeling method for the human upper limb.