Peterka Robert J
Biomedical Engineering Division, Oregon Health & Science University, OHSU West Campus, 505 NW 185th Avenue, Beaverton, OR 97006, USA.
J Physiol Paris. 2009 Sep-Dec;103(3-5):149-58. doi: 10.1016/j.jphysparis.2009.08.001. Epub 2009 Aug 7.
There is considerable recent interest in developing humanoid robots. An important substrate for many motor actions in both humans and biped robots is the ability to maintain a statically or dynamically stable posture. Given the success of the human design, one would expect there are lessons to be learned in formulating a postural control mechanism for robots. In this study we limit ourselves to considering the problem of maintaining upright stance. Human stance control is compared to a suggested method for robot stance control called zero moment point (ZMP) compensation. Results from experimental and modeling studies suggest there are two important subsystems that account for the low- and mid-frequency (DC to approximately 1Hz) dynamic characteristics of human stance control. These subsystems are (1) a "sensory integration" mechanism whereby orientation information from multiple sensory systems encoding body kinematics (i.e. position, velocity) is flexibly combined to provide an overall estimate of body orientation while allowing adjustments (sensory re-weighting) that compensate for changing environmental conditions and (2) an "effort control" mechanism that uses kinetic-related (i.e., force-related) sensory information to reduce the mean deviation of body orientation from upright. Functionally, ZMP compensation is directly analogous to how humans appear to use kinetic feedback to modify the main sensory integration feedback loop controlling body orientation. However, a flexible sensory integration mechanism is missing from robot control leaving the robot vulnerable to instability in conditions where humans are able to maintain stance. We suggest the addition of a simple form of sensory integration to improve robot stance control. We also investigate how the biological constraint of feedback time delay influences the human stance control design. The human system may serve as a guide for improved robot control, but should not be directly copied because the constraints on robot and human control are different.
最近，人们对开发类人机器人有着浓厚的兴趣。人类和双足机器人许多运动动作的一个重要基础是保持静态或动态稳定姿势的能力。鉴于人类设计的成功，人们期望在为机器人制定姿势控制机制时能学到一些经验教训。在本研究中，我们仅限于考虑保持直立姿势的问题。将人类的姿势控制与一种名为零力矩点（ZMP）补偿的机器人姿势控制建议方法进行了比较。实验和建模研究结果表明，有两个重要的子系统可以解释人类姿势控制的低频和中频（直流到约1Hz）动态特性。这些子系统是：（1）一种“感觉整合”机制，通过该机制，来自多个编码身体运动学（即位置、速度）的感觉系统的方向信息被灵活组合，以提供身体方向的总体估计，同时允许进行调整（感觉重新加权），以补偿不断变化的环境条件；（2）一种“用力控制”机制，该机制使用与动力学相关（即与力相关）的感觉信息来减少身体方向与直立方向的平均偏差。在功能上，ZMP补偿与人类似乎如何利用动力学反馈来修改控制身体方向的主要感觉整合反馈回路直接类似。然而，机器人控制中缺少灵活的感觉整合机制，这使得机器人在人类能够保持姿势的情况下容易出现不稳定。我们建议添加一种简单形式的感觉整合来改善机器人的姿势控制。我们还研究了反馈时间延迟的生物学限制如何影响人类姿势控制设计。人类系统可以作为改进机器人控制的指南，但不应直接照搬，因为机器人和人类控制的限制是不同的。
