Matsutani Yuki, Tahara Kenji, Kino Hitoshi
Department of Robotics, Faculty of Engineering, Kindai University, Higashi-Hiroshima, Japan.
Department of Mechanical Engineering, Faculty of Engineering, Kyushu University, Fukuoka, Japan.
Front Robot AI. 2021 Sep 27;8:699792. doi: 10.3389/frobt.2021.699792. eCollection 2021.
This study proposes two novel methods for determining the muscular internal force (MIF) based on joint stiffness, using an MIF feedforward controller for the musculoskeletal system. The controller was developed in a previous study, where we found that it could be applied to achieve any desired end-point position without the use of sensors, by providing the MIF as a feedforward input to individual muscles. However, achieving motion with good response and low stiffness using the system, posed a challenge. Furthermore, the controller was subject to an ill-posed problem, where the input could not be uniquely determined. We propose two methods to improve the control performance of this controller. The first method involves determining a MIF that can independently control the response and stiffness at a desired position, and the second method involves the definition of an arbitrary vector that describes the stiffnesses at the initial and desired positions to uniquely determine the MIF balance at each position. The numerical simulation results reported in this study demonstrate the effectiveness of both proposed methods.
本研究基于关节刚度提出了两种用于确定肌肉内力（MIF）的新方法，使用了一种用于肌肉骨骼系统的MIF前馈控制器。该控制器是在之前的一项研究中开发的，在该研究中我们发现，通过将MIF作为前馈输入提供给各个肌肉，无需使用传感器即可应用该控制器来实现任何所需的端点位置。然而，使用该系统实现具有良好响应和低刚度的运动带来了挑战。此外，该控制器存在一个不适定问题，即输入无法唯一确定。我们提出了两种方法来提高该控制器的控制性能。第一种方法涉及确定一个能够在期望位置独立控制响应和刚度的MIF，第二种方法涉及定义一个任意向量，该向量描述初始位置和期望位置的刚度，以唯一确定每个位置的MIF平衡。本研究报告的数值模拟结果证明了所提出的两种方法的有效性。
