【摘要】 传统割草机器人轨迹规划未能规划出最佳轨迹,导致规划能力较低,园林实施全方位割草作业效率降低。提出基于大数据的园林割草机器人轨迹规划方法。将CCD摄像头安装于割草机器人,检测草坪区域,分辨出草坪与非草坪区域;复杂环境下通过构建机器人运动模型,操控割草机器人,通过FPGA与神经网络相结合,调整权值来定位与导航机器人运动路线,规划出割草机器人运行的最佳轨迹;通过实验证明,所提方法可以准确穿越障碍物,具有精准的运动轨迹,并且适用于任何复杂园林环境,为城市园林绿化提供了更加便捷的方式。更多还原

【Abstract】 Traditionally, the mowing robot is failed to plan the best trajectory, resulting in low planning capacity and low efficiency of omni-directional mowing operations in garden. Therefore, a trajectory planning method for garden mowing robot based on big data was proposed. The CCD camera was installed on the mowing robot to detect the lawn region and distinguish between lawn region and non-lawn region. In complex environment, the robot motion model was constructed and the mowing robot was controlled. In addition, FPGA and neural network were combined to adjust the weights for positioning and navigating the motion path of robot, and thus to plan the optimal trajectory of the mowing robot. Simulation results prove that the proposed method can make the robot negotiate obstacles accurately, and the robot has accurate motion trajectory, so this method is suitable for any complex garden environment, which provides a more convenient way for urban gardening.更多还原