果园滑动转向机器人轮胎动力学参数实时估计方法

受果园路面起伏及轮胎附着能力变化影响,滑动转向轮式机器人轮胎的垂直载荷及侧向力参数变化大且难以实时估计,针对现有滑动转向控制器设计时对轮胎动力学参数进行简化,从而导致机器人姿态控制稳定性低的问题,本文提出了非铺装路面滑动转向轮式机器人轮胎垂直载荷实时估计方法和轮胎驱动力实时估计及优化分配算法。首先,提出了适用于滑动转向过程静力学计算的理想平面以及基于该平面的四轮垂直载荷估计方法;其次,提出了基于Fiala轮胎动力学模型的小侧偏角侧向力估计方法;再次,建立了滑动转向轮式机器人坡道稳态动力学方程和轮胎实时驱动力估计方法;最后,基于轮胎利用率构造轮胎驱动力最优实时分配模型。为验证本文方法,建立了基于ADAMS的滑动转向轮式机器人动力学模型进行对比验证,并且对垂直载荷以及侧向力估计方法搭建了检测装置进行实际验证。实际验证结果表明,轮胎垂直载荷实时估计方法准确率为95%以上,侧向力实时估计方法准确率为85%以上,基于轮胎垂直载荷以及侧向力的轮胎驱动力优化方法使轮胎利用率从96.25%降低至93.75%,提高了轮胎附着裕量和姿态控制稳定性。

Real-time Estimation Method of Tire Dynamics Parameters for Sliding Steering Robots in Orchards

The vertical load and lateral force parameters of sliding steering wheeled robot tires vary greatly and are difficult to estimate in real time due to the influence of orchard road surface undulations and tire adhesion capacity changes. The existing sliding steering controller is designed to simplify the tire dynamics parameters, which leads to the problem of low stability of robot attitude control. A real-time estimation method for the vertical load of sliding steering wheeled robot tires on unpaved roads and an algorithm for real-time estimation and optimal distribution of tire driving force were proposed. Firstly, an ideal plane for the static calculation of the sliding steering process and a four-wheel vertical load estimation method based on this plane were proposed; secondly, a small lateral deflection angle lateral force estimation method based on the Fiala wheel-tire dynamics model was proposed; and the steady-state dynamics equations of the sliding steering wheeled robot ramp and the real-time tire drive force estimation method were established; finally, the optimal real-time distribution model of the driving force was constructed based on the tire utilization rate. In order to verify the method, an ADAMS-based sliding steering wheeled robot dynamics model was developed for comparison and a testing device was built to verify the vertical load and lateral force estimation methods. The results showed that the accuracy of the real-time tire vertical load estimation method was more than 95% and the accuracy of the real-time lateral force estimation method was more than 85%, and the tire drive force optimization method based on the tire vertical load and lateral force reduced the tire utilization rate from 96.25% to 93.75%, which improved the tire adhesion margin and attitude control stability.