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Towards Robust Wheel-Legged Biped Robot System: Combining Feedforward and Feedback Control

机译:朝向强大的车轮腿部双方机器人系统:结合前馈和反馈控制

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This paper discusses the combination of model-based feedforward and feedback controller for the hybrid wheel-legged robot. Uncertainties in the modeling parameters such as friction coefficients, inertia matrices, and position of CoM can bring negative effects in the performance of model-based motion controllers. The ability of a control system to compensate for unforeseen circumstances is not only utilitarian but essential if one wishes to bring the robotic systems into the real world. To develop such a robust motion controller for the wheeled biped robot, we present the design and implementation of a nonlinear feedforward controller together with linearized feedback LQR to control the robot on a flat surface. This study investigates the controller performance: feedback, feedforward, and the combined in simulations and also with the real wheel-legged robot. Furthermore, the Extended Kalman Filter (EKF) is implemented to estimate the system states and reduce the sensor noise of the real robot.
机译:本文讨论了混合轮腿机器人模型的馈电和反馈控制器的组合。诸如摩擦系数,惯性矩阵等建模参数中的不确定性可以在基于模型的运动控制器的性能下带来负面影响。控制系统弥补无法预料的情况的能力不仅是功利,而且如果一个人希望将机器人系统带入现实世界。为了开发用于轮式双面机器人的这种鲁棒运动控制器,我们将非线性前馈控制器的设计和实现以及线性化反馈LQR一起提供,以控制平面上的机器人。本研究调查了控制器性能:反馈,馈电和模拟中的组合,也与真正的轮腿机器人相结合。此外,实施扩展的卡尔曼滤波器(EKF)以估计系统状态并降低真实机器人的传感器噪声。

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