移动机器人滑移补偿的滚动时域估计与结构噪声阻塞控制
Receding horizon estimation and control with structured noise blocking for mobile robot slip compensation
摘要：
在变化和不确定的地形条件下的控制领域的机器人自主导航提出了一个挑战。在线估计的车轮-地面滑移特性是必不可少的，以产生准确的控制预测所需的跟踪轨迹在越野环境。滚动时域估计（RHE）提供了一个强大的框架约束估计，并结合滚动时域控制（RHC），产生一个自适应优化为基础的控制方法。目前，这种方法假设滑动是恒定的估计范围内，而我们提出的结构化阻塞方法放松了这一假设，从而改善了状态和参数估计。我们演示和比较这种方法在模拟中的性能，并提出了一个阻塞策略，以改善在滚动时域估计和控制（RHEC）上下文中应用噪声阻塞遇到的一些限制。
英文摘要：
The control of field robots in varying and uncertain terrain conditions presents a challenge for autonomous navigation. Online estimation of the wheel-terrain slip characteristics is essential for generating the accurate control predictions necessary for tracking trajectories in off-road environments. Receding horizon estimation (RHE) provides a powerful framework for constrained estimation, and when combined with receding horizon control (RHC), yields an adaptive optimisation-based control method. Presently, such methods assume slip to be constant over the estimation horizon, while our proposed structured blocking approach relaxes this assumption, resulting in improved state and parameter estimation. We demonstrate and compare the performance of this method in simulation, and propose an overlapping-block strategy to ameliorate some of the limitations encountered in applying noise-blocking in a receding horizon estimation and control (RHEC) context.
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