IEEE Trans Biomed Eng. 2018 Feb;65(2):307-318. doi: 10.1109/TBME.2017.2764630. Epub 2017 Oct 19.
This paper proposes an operational task space formalization of constrained musculoskeletal systems, motivated by its promising results in the field of robotics.
The change of representation requires different algorithms for solving the inverse and forward dynamics simulation in the task space domain. We propose an extension to the direct marker control and an adaptation of the computed muscle control algorithms for solving the inverse kinematics and muscle redundancy problems, respectively.
Experimental evaluation demonstrates that this framework is not only successful in dealing with the inverse dynamics problem, but also provides an intuitive way of studying and designing simulations, facilitating assessment prior to any experimental data collection.
The incorporation of constraints in the derivation unveils an important extension of this framework toward addressing systems that use absolute coordinates and topologies that contain closed kinematic chains. Task space projection reveals a more intuitive encoding of the motion planning problem, allows for better correspondence between observed and estimated variables, provides the means to effectively study the role of kinematic redundancy, and most importantly, offers an abstract point of view and control, which can be advantageous toward further integration with high level models of the precommand level.
Task-based approaches could be adopted in the design of simulation related to the study of constrained musculoskeletal systems.
受机器人领域中取得的有前景的成果启发，本文提出了一种受约束肌肉骨骼系统的操作任务空间形式化方法。
表示的改变需要在任务空间域中解决逆动力学和正向动力学模拟的不同算法。我们提出了直接标记控制的扩展，并分别对计算肌肉控制算法进行了适应，以解决运动学逆解和肌肉冗余问题。
实验评估表明，该框架不仅成功地解决了逆动力学问题，而且还提供了一种直观的方法来研究和设计模拟，便于在任何实验数据收集之前进行评估。
在推导中包含约束条件揭示了该框架的一个重要扩展，使其能够解决使用绝对坐标和包含闭式运动链的拓扑结构的系统。任务空间投影揭示了运动规划问题更直观的编码方式，允许更好地对应观测变量和估计变量，提供了有效研究运动学冗余作用的手段，最重要的是，提供了一种抽象的观点和控制方式，这对于与预命令级别的高级模型进一步集成可能是有利的。
基于任务的方法可以应用于与受约束肌肉骨骼系统研究相关的仿真设计。
