用路径积分与盐化矩阵解决接触型混合系统的状态估计难题
Path Integral Particle Filtering for Hybrid Systems via Saltation Matrices
- 基于最优控制的粒子滤波，利用盐化矩阵建模接触时的不确定传播
- 在弹跳球和弹簧倒立摆上验证，对异常值和非高斯噪声鲁棒
- 适合需要精确处理间歇接触的机器人与航天器状态估计
对于经历与环境间歇性接触的混合系统（如外星探测机器人、执行对接操作的卫星），状态估计因接触过程中的离散不确定性传播而极具挑战。本文提出一种基于最优控制的粒子滤波方法，利用盐化矩阵刻画接触事件中的不确定性传播。通过路径积分滤波框架，该方法利用平滑与最优控制之间的对偶性，使算法对异常值具有鲁棒性，能适应非高斯噪声分布，并有效处理混合系统中的复杂接触动力学。为验证所提方法的有效性与一致性，本文在随机动力学模型（包括弹跳球与弹簧加载倒立摆）上与强基线方法进行对比测试。
原文摘要 · Abstract (English)
State estimation for hybrid systems that undergo intermittent contact with their environments, such as extraplanetary robots and satellites undergoing docking operations, is difficult due to the discrete uncertainty propagation during contact. To handle this propagation, this paper presents an optimal-control-based particle filtering method that leverages saltation matrices to map out uncertainty propagation during contact events. By exploiting a path integral filtering framework that exploits the duality between smoothing and optimal control, the resulting state estimation algorithm is robust to outlier effects, flexible to non-Gaussian noise distributions, and handles challenging contact dynamics in hybrid systems. To evaluate the validity and consistency of the proposed approach, this paper tests it against strong baselines on the stochastic dynamics generated by a bouncing ball and spring loaded inverted pendulum.
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