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A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots

机译：移动机器人轮式运动控制的多模式实时地形参数估计方法

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摘要

For motion control of wheeled planetary rovers traversing on deformable terrain, real-time terrain parameter estimation is critical in modeling the wheel-terrain interaction and compensating the effect of wheel slipping. A multi-mode real-time estimation method is proposed in this paper to achieve accurate terrain parameter estimation. The proposed method is composed of an inner layer for real-time filtering and an outer layer for online update. In the inner layer, sinkage exponent and internal frictional angle, which have higher sensitivity than that of the other terrain parameters to wheel-terrain interaction forces, are estimated in real time by using an adaptive robust extended Kalman filter (AREKF), whereas the other parameters are fixed with nominal values. The inner layer result can help synthe-size the current wheel-terrain contact forces with adequate precision, but has limited prediction capability for time-variable wheel slipping. To improve estimation accuracy of the result from the inner layer, an outer layer based on recursive Gauss-Newton (RGN) algorithm is introduced to refine the result of real-time filtering according to the innovation contained in the history data. With the two-layer structure, the proposed method can work in three fundamental estimation modes: EKF, REKF and RGN, making the method applicable for flat, rough and non-uniform terrains. Simulations have demonstrated the effectiveness of the proposed method under three terrain types, showing the advantages of introducing the two-layer structure.
机译：对于在变形地形上行走的带轮行星漫游车的运动控制，实时地形参数估计对于建模轮-地相互作用和补偿轮滑的影响至关重要。提出一种多模式实时估计方法，以实现准确的地形参数估计。所提出的方法由用于实时过滤的内层和用于在线更新的外层组成。在内层，通过使用自适应鲁棒扩展卡尔曼滤波器（AREKF）实时估算下沉指数和内摩擦角，这些下沉指数和内摩擦角比其他地形参数对轮-土相互作用力具有更高的灵敏度。参数用标称值固定。内层结果可以帮助以足够的精度合成当前的车轮-地面接触力的大小，但是对于随时间变化的车轮打滑的预测能力有限。为了提高内层结果的估计精度，引入了基于递归高斯牛顿（RGN）算法的外层，以根据历史数据中包含的创新改进实时过滤的结果。该方法具有两层结构，可以在EKF，REKF和RGN三种基本估计模式下工作，使得该方法适用于平坦，粗糙和非均匀地形。仿真证明了该方法在三种地形类型下的有效性，显示了引入两层结构的优势。

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