This work addresses the synergistic fusion of optimal control simulations and marker-based optical measurements of human motion. The latter is a widespread capturing technology in biomechanics and movement science. In the context of optimal control simulations, the idea is to improve the computational performance by using a realistic initial guess and to increase the realism of the simulated motion through data-guiding. In the context of motion capturing, the idea is to use biomechanical simulations in order to maintain accurate capturings also with reduced measurement frequencies and points. This would greatly improve the usability of such systems in terms of setup time and wearing comfort. In this work, we investigate different methods for combining physical laws, 3D marker positions obtained from the optical system, and physiologically motivated objectives in an optimal control framework. Moreover, we explore the potential of obtaining reasonable results—in terms of motion trajectories and torques that are close to reference obtained from using all available information—with a reduced measurement frequency and a reduced number of markers. The tests are performed on a human steering and throwing motion, where a human arm was captured with seven retroreflective markers at \(120\text{ Hz}\). Our results show, that a significant reduction of exploited measurements still provides feasible simulation results in our proposed method, given that the physiologically motivated objective reflects the actual movement. Furthermore, it turns out that neglecting markers close to the shoulder has less influence on the simulation results than neglecting markers close to the hand.

中文翻译：

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基于光学数据的人体运动最优控制仿真

这项工作解决了最佳控制仿真和基于标记的人体运动光学测量的协同融合问题。后者是生物力学和运动科学中广泛使用的捕获技术。在最佳控制仿真的情况下，其思想是通过使用逼真的初始猜测来提高计算性能，并通过数据指导来提高仿真运动的真实性。在运动捕捉的背景下，该想法是使用生物力学模拟，以便在减少测量频率和测量点的同时保持精确的捕捉。就设置时间和佩戴舒适度而言，这将大大提高此类系统的可用性。在这项工作中，我们研究了将物理定律，从光学系统获得的3D标记位置，最佳控制框架中具有生理动机的目标。此外，我们探索了获得合理结果的潜力-在运动轨迹和扭矩方面均接近于使用所有可用信息所获得的参考值-减少了测量频率，减少了标记数量。测试是在人的转向和投掷动作下进行的，其中用7个逆向反射标记捕获了人的手臂。\（120 \ text {Hz} \）。我们的结果表明，考虑到生理动机的目标反映了实际的运动，在我们提出的方法中，利用测量值的显着减少仍然可以提供可行的模拟结果。此外，事实证明，忽略肩膀附近的标记对仿真结果的影响要比忽略手附近的标记对模拟结果的影响小。