论文标题
对具有平坦脚的人形机器人的浮动碱估计器的实验比较
An Experimental Comparison of Floating Base Estimators for Humanoid Robots with Flat Feet
论文作者
论文摘要
扩展的卡尔曼过滤是实现人形机器人浮动碱基估计的常见方法。这些过滤器依赖于惯性测量单元（IMU）和相对前向运动学的测量值来估计基础位置和方向及其线性速度以及脚部位置和方向的增强状态，从而给他们姓名平坦的过滤器。但是，仅部分测量值的可用性通常会提出过滤器设计中一致性的问题。在本文中，我们根据状态选择，观察，矩阵谎言组误差和对滤波器一致性和轨迹错误评估的系统动力学对最先进的平脚过滤器进行实验比较。比较是在ICUB类人体平台上进行的模拟和现实世界实验进行的。
Extended Kalman filtering is a common approach to achieve floating base estimation of a humanoid robot. These filters rely on measurements from an Inertial Measurement Unit (IMU) and relative forward kinematics for estimating the base position-and-orientation and its linear velocity along with the augmented states of feet position-and-orientation, thus giving them their name, flat-foot filters. However, the availability of only partial measurements often poses the question of consistency in the filter design. In this paper, we perform an experimental comparison of state-of-the-art flat-foot filters based on the representation choice of state, observation, matrix Lie group error and system dynamics evaluated for filter consistency and trajectory errors. The comparison is performed over simulated and real-world experiments conducted on the iCub humanoid platform.
