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Model predictive obstacle avoidance control for omni-directional mobile robots based on fuzzy potential method

机译:基于模糊势方法的全方位移动机器人模型预测避障控制

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In this paper, we propose an optimal obstacle avoidance control method with translational and rotational motion for omni-directional mobile robots based on model predictive control (MPC) modifying fuzzy potential method (FPM). The reference path is generated by FPM considering the shape and the size of the robot, but it might vary steeply because the vehicle dynamics is not considered explicitly. To resolve this issue, the robot tracks the path while modifying it by optimization using MPC which computes an optimal input under prediction based on the dynamics until finite-time future in order to achieve smooth and efficient obstacle avoidance. The performance of the method is verified through comparative simulations.
机译:本文提出了一种基于模型预测控制(MPC)修正模糊势方法(FPM)的全方位移动机器人最优的平移和旋转运动避障控制方法。参考路径是由FPM考虑机器人的形状和大小而生成的,但由于未明确考虑车辆动力学,因此参考路径可能会急剧变化。为了解决这个问题,机器人在跟踪路径的同时通过使用MPC进行优化来对其进行修改,MPC会根据动态计算预测的最佳输入,直到有限时间的将来,以实现平稳高效的避障。通过比较仿真验证了该方法的性能。

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