用工业机器人进行等速腿部伸展训练

M. Kolditz, Thivaharan Albin, K. Albracht, G. Brüggemann, D. Abel
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引用次数: 4

摘要

腿伸肌的阻力训练是康复和预防肌肉骨骼疾病(如髋关节或膝关节疾病和骨质疏松症)的重要干预措施。现有的训练设备既无法优化运动轨迹,也无法控制肌肉骨骼系统结构的负荷。为了克服这些限制,开发了一个用于开发新训练场景的实验研究平台,该平台使用工业机器人来实现最大的灵活性,并结合动力学和运动学数据以及用于估计目标结构载荷的肌肉骨骼模型。本文的重点在于等速运动的实施,即匀速的伸腿和屈腿。需要为机器人规划一个在两点之间平滑过渡的力触发轨迹。提出了一种使用连续多项式的算法。它由三部分组成。首先,通过直观的定义,如起点和终点或所需速度和最小阻力,在笛卡尔空间中规划轨迹。使用OpenSim和研究平台模型可以对轨迹进行可视化和优化,这使得系统可以用于机器人领域的非专家。其次,利用相邻两点间关节速度的三阶多项式,从规划点生成关节空间中的光滑轨迹;第三,轨迹与末端执行器测量的力相适应,因为如果用户施加的力足够大,机器人只应该沿着轨迹移动。此外,该算法易于扩展到具有可定义的位置和速度轮廓的任意力触发运动。
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Isokinematic leg extension training with an industrial robot
Resistance training of the leg extensor muscles is an important intervention in rehabilitation and prevention of musculoskeletal disorders such as hip or knee arthrosis and osteoporosis. With current training equipment, neither the exercise trajectory can be optimized nor the loadings on structures of the musculoskeletal system can be controlled. To overcome these limitations an experimental research platform for the development of new training scenarios is developed using an industrial robot for maximum flexibility together with kinetic and kinematic data and musculoskeletal models for estimating loadings on target structures. The focus of this paper lies on the implementation of isokinematic exercise, i.e. leg extension and flexion with constant velocity. A force triggered trajectory with smooth transitions between two points needs to be planned for the robot. An algorithm which uses continuous polynomials is proposed. It consists of three parts. First, the trajectory is planned in Cartesian space by intuitive definitions of e.g. start and end point or desired velocity and minimum resistive force. The trajectory can be visualized and optimized using OpenSim together with a model of the research platform, which makes the system usable for non experts in the field of robotics. Second, a smooth trajectory in joint space is generated from the planning points, using a third order polynomial for joint velocities between two adjacent points. Third, the trajectory is adapted to the measured force at the end effector, as the robot should only move along the trajectory, if the applied force by the user is high enough. The proposed algorithm is furthermore easily expandable to arbitrary force triggered motions with definable position and velocity profiles.
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