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首页> 外文期刊>International Journal of Advanced Robotic Systems >Fuzzy Vector Field Orientation Feedback Control-Based Slip Compensation for Trajectory Tracking Control of a Four Track Wheel Skid-steered Mobile Robot
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Fuzzy Vector Field Orientation Feedback Control-Based Slip Compensation for Trajectory Tracking Control of a Four Track Wheel Skid-steered Mobile Robot

机译：基于模糊矢量场方向反馈控制的滑移补偿的四履带滑移移动机器人轨迹跟踪控制

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摘要

Skid-steered mobile robots have been widely used in exploring unknown environments and in military applications. In this paper, the tuning fuzzy Vector Field Orientation (FVFO) feedback control method is proposed for a four track wheel skid-steered mobile robot (4-TW SSMR) using flexible fuzzy logic control (FLC). The extended Kalman filter is utilized to estimate the positions, velocities and orientation angles, which are used for feedback control signals in the FVFO method, based on the AHRS kinematic motion model and velocity constraints. In addition, in light of the wheel slip and the braking ability of the robot, we propose a new method for estimating online wheel slip parameters based on a discrete Kalman filter to compensate for the velocity constraints. As demonstrated by our experimental results, the advantages of the combination of the proposed FVFO and wheel slip estimation methods overcome the limitations of the others in the trajectory tracking control problem for a 4-TW SSMR.
机译：滑移式移动机器人已广泛用于探索未知环境和军事应用。本文提出了一种采用柔性模糊逻辑控制（FLC）的四履带轮滑移式移动机器人（4-TW SSMR）的调谐模糊矢量场定向（FVFO）反馈控制方法。扩展的卡尔曼滤波器用于基于AHRS运动学运动模型和速度约束来估计FVFO方法中用于反馈控制信号的位置，速度和方向角。此外，鉴于车轮打滑和机器人的制动能力，我们提出了一种基于离散卡尔曼滤波器来补偿速度约束的在线车轮打滑参数估计的新方法。如我们的实验结果所示，所提出的FVFO和车轮滑移估计方法相结合的优势克服了4-TW SSMR的轨迹跟踪控制问题中其他方法的局限性。

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