Legged Robot State Estimation With Dynamic Contact Event Information
Legged Robot State Estimation With Dynamic Contact Event Information
复制标题
利用动态接触事件信息进行腿式机器人状态估计
DOI：
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复制
发表时间：
2021
影响因子：
5.2
通讯作者：
Hae
中科院分区：
文献类型：
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作者：
Joon;Seungwoo Hong;Gwanghyeon Ji;S. Jeon;Jemin Hwangbo;Jun;Hae
这封信提出了一种腿式机器人的状态估计算法，将问题定义为最大后验（MAP）估计问题，并用高斯-牛顿算法求解该问题。此外，采用Schur Complement方法进行边缘化来制作固定大小的问题。成本函数的每个分量及其雅可比行列式都是利用 SO(3) 流形结构导出的，同时我们用标称状态和变分重新参数化状态，以使线性代数和向量微积分得到正确应用。此外，提出了一种滑移抑制方法来减少运动学模型故障建模的错误影响。通过在各种环境下的真实机器人实验中与不变扩展卡尔曼滤波器（IEKF）进行比较，验证了所提出的算法。
This letter presents a state estimation algorithm for the legged robot by defining the problem as a Maximum A Posteriori (MAP) estimation problem and solving the problem with the Gauss-Newton algorithm. Moreover, marginalization by the Schur Complement method is adopted to make a fixed size problem. Each component of the cost function and its Jacobian are derived utilizing the SO(3) manifold structure, while we reparameterize the state with nominal state and variation to make linear algebra and vector calculus applied properly. Furthermore, a slip rejection method is proposed to reduce the erroneous effect of fault modeling of kinematics models. The proposed algorithm is verified by comparison with the Invariant Extended Kalman Filter (IEKF) in real robot experiments on various environments.
影响因子：
9.2
作者：
Hartley, Ross;Ghaffari, Maani;Grizzle, Jessy W.
通讯作者：
Grizzle, Jessy W.