谢德胜, 徐友春, 万剑, 韩栋斌, 陆峰. 基于RTK-GPS的轮式移动机器人轨迹跟随控制[J]. 机器人, 2017, 39(2): 221-229. DOI: 10.13973/j.cnki.robot.2017.0221
引用本文: 谢德胜, 徐友春, 万剑, 韩栋斌, 陆峰. 基于RTK-GPS的轮式移动机器人轨迹跟随控制[J]. 机器人, 2017, 39(2): 221-229. DOI: 10.13973/j.cnki.robot.2017.0221
XIE Desheng, XU Youchun, WAN Jian, HAN Dongbin, LU Feng. Trajectory Tracking Control of Wheeled Mobile Robots Based on RTK-GPS[J]. ROBOT, 2017, 39(2): 221-229. DOI: 10.13973/j.cnki.robot.2017.0221
Citation: XIE Desheng, XU Youchun, WAN Jian, HAN Dongbin, LU Feng. Trajectory Tracking Control of Wheeled Mobile Robots Based on RTK-GPS[J]. ROBOT, 2017, 39(2): 221-229. DOI: 10.13973/j.cnki.robot.2017.0221

基于RTK-GPS的轮式移动机器人轨迹跟随控制

Trajectory Tracking Control of Wheeled Mobile Robots Based on RTK-GPS

  • 摘要: 针对轮式移动机器人的轨迹跟随问题,提出了一种基于RTK-GPS(real-time kinematic GPS)的轨迹跟随控制方法.首先,将GPS(全球定位系统)轨迹地图和机器人实时的RTK-GPS经提出的坐标转换模型转换到同一平面坐标系.因为RTK-GPS受干扰时会出现GPS点跳变,所以采用标准卡尔曼滤波器进行滤波,用最优估计值作为机器人真实的位置.通过遍历轨迹地图找寻初始最近目标点,然后不断更新目标点并采用角度偏差比例-微分控制器实时控制机器人的转向,实现了轮式移动机器人的轨迹跟随.最后,在改型轮式移动机器人上进行了实验,实验结果表明整体算法具有较高的可靠度,跟随具有代表性的“蛇”形轨迹和“8”字形轨迹时分别将偏差控制在0.42 m以内和0.67 m以内.

     

    Abstract: Aiming at the trajectory tracking problem of wheeled mobile robots, a trajectory tracking control method based on RTK-GPS (real-time kinematic GPS) is proposed. Firstly, the GPS (global positioning system) trajectory map and the real-time RTK-GPS of the robot are converted to the same plane coordinate system through the proposed coordinate conversion model. Secondly, GPS trip points occur when RTK-GPS is disturbed, so the optimal estimate after filtering with standard Kalman filter is used as the robot's true position. The trajectory map is traversed to find the initial nearest target point, then the target point is updated continuously, and the proportional-derivative controller of angular deviation is adopted to control the steering of the robot in real time. By this way, the trajectory tracking of the wheeled mobile robot is achieved. The experiment is conducted on a modified wheeled mobile robot. Experimental results show that the algorithm has a high reliability. The deviations when tracking the snake-shaped and 8-shaped trajectories are within 0.42 m and 0.67m respectively.

     

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