The extent of vibrations experienced by a vehicle driving over natural terrain defines its ride quality. Generally, surface irregularities, ranging from single discontinuities to random variations of the elevation profile, act as a major source of excitation that induces vibrations in the vehicle body through the tire-soil interaction and suspension system. Therefore, the ride response of off-road vehicles is tightly connected with the ground properties. The objective of this research is to develop a model-based observer that estimates automatically terrain parameters using available onboard sensors. Two acceleration signals, one coming from the vehicle body and one from the wheel suspension, are fed into a dynamic vehicle model that takes into account tire/terrain interaction to estimate ground properties. To solve the resulting nonlinear simultaneous state and parameter estimation problem, the cubature Kalman filter is used, which is shown to outperform the standard extended Kalman filter in terms of accuracy and stability. An extensive set of simulation tests is presented to assess the performance of the proposed estimator under various surface roughness and deformability conditions. Results show the potential of the proposed observer to estimate automatically terrain properties during operations that could be implemented onboard of a general family of intelligent vehicles, ranging from off-road high-speed passenger cars to lightweight and low-speed planetary rovers.

中文翻译：

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通过车辆振动测量和体积卡尔曼滤波的地形估计

车辆在自然地形上行驶所经历的振动程度决定了其乘坐质量。通常，表面不规则，从单一的不连续性到高度轮廓的随机变化，是主要的激励源，通过轮胎-土壤相互作用和悬架系统在车身中引起振动。因此，越野车的乘坐响应与地面特性密切相关。这项研究的目的是开发一种基于模型的观测器，该观测器使用可用的机载传感器自动估计地形参数。两个加速度信号，一个来自车身，一个来自车轮悬架，被输入到动态车辆模型中，该模型考虑了轮胎/地形相互作用来估计地面特性。为了解决由此产生的非线性同时状态和参数估计问题，使用了容积卡尔曼滤波器，它在准确性和稳定性方面优于标准扩展卡尔曼滤波器。提出了一组广泛的模拟测试，以评估所提出的估计器在各种表面粗糙度和变形条件下的性能。结果显示了提议的观测器在操作期间自动估计地形属性的潜力，这些操作可以在一般智能车辆系列上实施，从越野高速乘用车到轻型和低速行星漫游车。提出了一组广泛的模拟测试，以评估所提出的估计器在各种表面粗糙度和变形条件下的性能。结果显示了提议的观测器在操作期间自动估计地形属性的潜力，这些操作可以在一般智能车辆系列上实施，从越野高速乘用车到轻型和低速行星漫游车。提出了一组广泛的模拟测试，以评估所提出的估计器在各种表面粗糙度和变形条件下的性能。结果显示了提议的观测器在操作期间自动估计地形属性的潜力，这些操作可以在一般智能车辆系列上实施，从越野高速乘用车到轻型和低速行星漫游车。