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Mobile Robot Based Autonomous Selection of Fuzzy-PID Behavior and Visual Odometry for Navigation and Avoiding Barriers in the Plant Environment

机译:基于移动机器人的自主选择模糊PID行为以及植物环境中的导航障碍

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This study aims to assess navigation and obstacle avoidance by autonomous mobile robots in plant environments using Fuzzy-PID behavior selection algorithms and visual odometry. The research variables are height, width, and distance. The PID set point is 80, the proportional constant value is 0.5, the integral constant value is 0.45, and the derivative constant value is 0.6. Mobile robots were tested using model 1 and model 2 designs on different patterns with as many as 9 obstacles. The result of the ultrasonic sensor testing is that the overall accuracy was 99.71%. For each of the category, the Pixy camera testing results in block 1 having an accuracy of 77.44%, block 2 97.88%, and block 3 85.88%. Mobile robot testing on the same model shows an increase in accuracy after the distance input value on the fuzzy is enlarged. Future research can use machine learning methods.
机译:本研究旨在使用模糊PID行为选择算法和视觉径管在植物环境中通过自主移动机器人评估导航和障碍物。研究变量是高度,宽度和距离。 PID设定点为80,比例常数值为0.5,积分恒定值为0.45,衍生恒定值为0.6。使用型号1和模型2设计进行测试移动机器人,在不同的模式下设计,具有多达9个障碍物。超声波传感器测试的结果是整体准确性为99.71%。对于每个类别,Pixy摄像机测试结果在块1中,精度为77.44%,块2 97.8%,块385.88%。在相同模型上的移动机器人测试显示了在模糊上的距离输入值放大后的准确性提高。未来的研究可以使用机器学习方法。

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