13自由度气动机器人实现高重复运动，数据驱动控制优于传统方法
Dynamic Properties and Motion Reproducibility of a Compact Pneumatically Actuated Humanoid Upper Body for Data-Driven Control
- 基于多层感知机+时延补偿，用随机数据训练气动臂轨迹控制
- 系统运动重复性高，数据驱动控制器轨迹跟踪精度显著优于PID
- 适合研究高自由度气动人形机器人控制的学者与工程师
具有高自由度（DOF）的气动仿人机器人在人机物理交互中潜力巨大，但其执行器固有的非线性使得精确控制极具挑战。本文开发了一种紧凑的13-DOF上肢人形机器人。为评估有效控制器的可行性，我们首先研究了系统的动态特性，如执行时延，并证实该系统表现出高度可重复的行为。基于这种可重复性，我们针对4-DOF手臂子系统实现了一个初步的数据驱动控制器，采用带显式时延补偿的多层感知机网络。该网络通过随机运动数据训练，生成压力指令以跟踪任意轨迹。与传统PID控制器的对比实验表明，数据驱动方法在轨迹跟踪性能上表现更优，凸显了其在复杂、高自由度气动机器人控制中的潜力。
原文摘要 · Abstract (English)
Pneumatically-actuated anthropomorphic robots with high degrees of freedom (DOF) offer significant potential for physical human-robot interaction. However, precise control of pneumatic actuators is challenging due to their inherent nonlinearities. This paper presents the development of a compact 13-DOF upper-body humanoid robot. To assess the feasibility of an effective controller, we first investigate its key dynamic properties, such as actuation time delays, and confirm that the system exhibits highly reproducible behavior. Leveraging this reproducibility, we implement a preliminary data-driven controller for a 4-DOF arm subsystem based on a multilayer perceptron with explicit time delay compensation. The network was trained on random movement data to generate pressure commands for tracking arbitrary trajectories. Comparative evaluations with a traditional PID controller demonstrate superior trajectory tracking performance, highlighting the potential of data-driven approaches for controlling complex, high-DOF pneumatic robots.
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