Main purpose of this project is to develop fundamental technology for assist robots to recover and maintain human motor skill and to extend scope of human activity. Our goal is to provide a system that adapts to its user’s personal behavior patterns in real-time. We aim to develop a continuous collaboration system between the assist robots and the user where both alternatively adjust to each other to maximize the system’s utility. To understand human movement, we recorded motion sequence of several tasks for different subjects using motion capture system. Through analysis of human motion data, we extracted a general model by rule-based approach. On the other hand, since such tasks are not feasible with static models, we investigate the potential benefit of supervised online learning in the task of online action classification and Deep Learning in the task of acquiring human motion. Finally, developed system was extended to show its potential effect in ergonomics and in assist robotics. GRAPHICAL ABSTRACT

中文翻译：

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用于理解人体运动的机器学习

该项目的主要目的是开发辅助机器人恢复和保持人类运动技能并扩展人类活动范围的基础技术。我们的目标是提供一个实时适应用户个人行为模式的系统。我们的目标是在辅助机器人和用户之间开发一个持续的协作系统，两者交替调整以最大限度地提高系统的效用。为了理解人体运动，我们使用运动捕捉系统记录了不同主题的多项任务的运动序列。通过对人体运动数据的分析，我们通过基于规则的方法提取了一个通用模型。另一方面，由于这些任务对于静态模型是不可行的，我们调查了监督在线学习在在线动作分类任务中和深度学习在获取人体动作任务中的潜在好处。最后，对开发的系统进行了扩展，以显示其在人体工程学和辅助机器人方面的潜在影响。图形概要