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Ground reaction force sensor fault detection and recovery method based on virtual force sensor for walking biped robots

机译:基于虚拟力传感器的步行两足机器人地面反作用力传感器故障检测与恢复方法

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This paper presents a novel method for ground force sensor faults detection and faulty signal reconstruction using Virtual force Sensor (VFS) for slow walking bipeds. The design structure of the VFS consists of two steps, the total ground reaction force (GRF) and its location estimation for each leg based on the center of mass (CoM) position, the leg kinematics, and the IMU readings is carried on in the first step. In the second step, the optimal estimation of the distributed reaction forces at the contact points in the feet sole of walking biped is carried on. For the optimal estimation, a constraint model is obtained for the distributed reaction forces at the contact points and the quadratic programming optimization method is used to solve for the GRF. The output of the VFS is used for fault detection and recovery. A faulty signal model is formed to detect the faults based on a threshold, and recover the signal using the VFS outputs. The sensor offset, drift, and frozen output faults are studied and tested. The proposed method detects and estimates the faults and recovers the faulty signal smoothly. The validity of the proposed estimation method was confirmed by simulations on 3D dynamics model of the humanoid robot SURALP while walking. The results are promising and prove themselves well in all of the studied fault cases.
机译:本文提出了一种使用虚拟力传感器(VFS)的慢速两足动物进行地面力传感器故障检测和故障信号重建的新方法。 VFS的设计结构包括两个步骤,总地面反作用力(GRF)及其根据质心(CoM)位置,腿部运动学和IMU读数在每条腿上进行的位置估计是在地面上进行的。第一步。在第二步中,对步行两足动物的脚底接触点处的分布反作用力进行最佳估计。对于最优估计,针对接触点处的分布反作用力获得约束模型,并使用二次规划优化方法求解GRF。 VFS的输出用于故障检测和恢复。形成故障信号模型以基于阈值检测故障,并使用VFS输出恢复信号。对传感器失调,漂移和冻结输出故障进行了研究和测试。所提出的方法可以检测和估计故障,并平稳地恢复故障信号。通过仿真人形机器人SURALP行走时的3D动力学模型,验证了所提出估计方法的有效性。结果是有希望的,并在所有研究的故障案例中证明了自己。

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