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Autonomous mobile robot model predictive control

机译:自主移动机器人模型预测控制

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摘要

This paper presents model predictive control of an autonomous vehicle. Simulation and experimental results have been shown and compared with input-output linearization method. The results obtained show that the MPC is an efficient method that allows for accurate control and navigation of an autonomous vehicle. Model based predictive control is tested in simulations for motion on an inclined plane. This is done to prepare future work regarding the avoidance of the violation of the smoothness condition for exact linearization, while at the same time by modifying the input commands the geometric path planning results are conserved. The approach is presented for the wheel-ground slippage and tip-over avoidance of the three-wheeled vehicle for inclined plane motion. A complete three-dimensional dynamic model using Newtonian dynamics is also presented. Simulation results using a three-wheeled vehicle built in our laboratory illustrate the performance of the proposed controller.
机译:本文提出了一种自动驾驶汽车的模型预测控制。给出了仿真和实验结果,并与输入输出线性化方法进行了比较。获得的结果表明,MPC是允许对自动驾驶车辆进行精确控制和导航的有效方法。在仿真中测试了基于模型的预测控制在倾斜平面上的运动。这样做是为了准备将来的工作,以避免为精确线性化而违反平滑条件,同时通过修改输入命令可以保存几何路径规划结果。提出了针对倾斜平面运动的三轮车辆的车轮-地面打滑和避免翻倒的方法。还提出了使用牛顿动力学的完整三维动力学模型。使用我们实验室内置的三轮车辆的仿真结果说明了所提出控制器的性能。

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