Exact and real-time kinematics model plays a very important role in the mobile robot motion control and path planning. Compared to the off-line model estimation, based on an Instantaneous Centers of Rotation (ICRs) based kinematic model of skid-steering, an Extend Kalman Filter (EKF) method is used to estimate ICRs values on specific terrain on line. Terrains are identified by introducing k-Nearest Neighbors (kNN) algorithm when the robot moves on different terrains. Based on terrain classification, an Adaptive Kalman Filter (AKF) is used to adjust the filter parameters. The simulation and experiment results show that this method can converge very fast and estimate the ICRs value accurately with 3 seconds.
吴耀,王田苗,王晓刚,刘淼. 基于自适应卡尔曼滤波的侧滑移动机器人运动模型估计[J]. 电子与信息学报, 2015, 37(12): 3016-3024.
Wu Yao, Wang Tian-miao, Wang Xiao-gang, Liu Miao. Kinematics Model Prediction of Skid-steering Robot Using Adaptive Kalman Filter Estimation. JEIT, 2015, 37(12): 3016-3024.
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