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Polyhedral contact formation identification for autonomous compliant motion: exact nonlinear bayesian filtering

机译:多面体接触形成识别,用于自主顺应运动:精确的非线性贝叶斯滤波

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摘要

This work presents new experimental results for the estimation of large position and orientation inaccuracies of contacting objects during force-controlled compliant motion. The estimation is based on position, velocity, and force measurements. The authors have described the contact modeling and presented some Kalman filter identification results for small inaccuracies. However, when dealing with larger inaccuracies, the nonlinear estimation problem remained unsolved. This problem has now been solved satisfactorily by applying a new Bayesian estimator. The Bayesian filter is valid for static systems (parameter estimation) with any kind of nonlinear measurement equation, subject to Gaussian measurement uncertainty and for a limited class of dynamic systems. Experimental results of this new filter are given for the estimation of the positions and orientations of contacting objects during the cube-in-corner assembly described in the first reference.
机译:这项工作提出了新的实验结果,用于估算受力控制的顺应运动期间接触物体的较大位置和方向不准确度。该估计基于位置,速度和力的测量结果。作者已经描述了接触模型,并提出了一些针对小误差的卡尔曼滤波器识别结果。但是,当处理较大的误差时,非线性估计问题仍未解决。现在,通过使用新的贝叶斯估计器可以令人满意地解决此问题。贝叶斯滤波器对于具有任何非线性测量方程的静态系统(参数估计)有效,受高斯测量不确定性的影响,并且对于一类有限的动态系统有效。给出了此新过滤器的实验结果,用于估算在第一个参考文献中描述的方角形立方体组装过程中接触对象的位置和方向。

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