基于惯性测量装置的人形步态低成本ZMP估计方法:概念与实验

R. Das, A. Chemori, Neelesh Kumar
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摘要

零力矩点估计与控制(ZMP)是两足机器人运动规划中广泛使用的概念,通常使用集成关节角编码器和足部力传感器进行测量。当前测量ZMP的方法包括内置接触式传感器,如关节编码器或仪表式脚力传感器。本文提出了一种利用基于惯性传感器的无线足部传感器模块(WFSM)计算仿人机器人ZMP的新方法。所开发的WFSMs绑在两足机器人的不同肢体上,实时测量下肢关节角度。采用平面双足模型,利用关节角轨迹转化为直角位置坐标,估计仿人机器人的ZMP位置。通过对不同现实生活步行场景的实验研究,提出了整个框架。由于模块基于肢体运动和倾斜工作,任何地面不平整都会自动反映在模块输出中。因此,这种测量过程对于需要在不平整的表面/室外地形上进行人形控制的应用来说是一种方便的方法。为了比较所提模型的性能,ZMP由机器人的内置足力传感器和关节编码器同时测量。统计检验表明,所提出的方法与集成编码器和足部力传感器之间存在高度线性相关(Pearson系数,r > 0.99)。结果表明,基于WFSM估计的ZMP是监测仿人机器人动态步态平衡的一种可行方法,在室外和不平整地形中具有潜在的应用前景
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A Novel Low-Cost ZMP Estimation Method for Humanoid Gait using Inertial Measurement Devices: Concept and Experiments
Estimation and control of Zero Moment Point (ZMP) is a widely used concept for planning the locomotion of bipedal robots and is commonly measured using integrated joint angle encoders and foot force sensors. Contemporary methods for ZMP measurement involve built-in contact sensors such as joint encoders or instrumented foot force sensors. This paper presents a novel approach for computing ZMP for a humanoid robot using inertial sensor-based wireless foot sensor modules (WFSM). The developed WFSMs, strapped at different limb segments of a bipedal robot, measure lower limb joint angles in real-time. The joint angle trajectories, further transformed into cartesian position coordinates, are used for estimating the ZMP positions of humanoid robots using the planar biped model. The whole framework is presented through experimental studies for different real-life walking scenarios. Since the modules work based on the limb motion and inclination, any ground unevenness would be automatically reflected in the module output. Hence, this measurement process can be a convenient method for applications requiring humanoid control on uneven surfaces/ outdoor terrains . To compare the performance of the proposed model, ZMP is simultaneously measured from inbuilt foot force sensors and joint encoders of the robot. Statistical tests exhibit a high linear correlation between the proposed method with integrated encoders and foot force sensors (Pearson’s coefficient, r > 0.99). Results indicate that ZMP estimated by WFSM is a viable method to monitor the dynamic gait balance of a humanoid robot and has potential application in outdoor and uneven terrains
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