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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:基于移动机器人的模糊-PID行为和视觉里程表的自主选择,用于工厂环境中的导航和避障

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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:这项研究旨在通过使用Fuzzy-PID行为选择算法和视觉里程表来评估工厂环境中的自主移动机器人的导航和避障。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,积分常数值为0.45,微分常数值为0.6。使用模型1和模型2设计了多达9个障碍物的不同模式的移动机器人。超声波传感器测试的结果是整体精度为99.71%。对于每个类别,Pixy相机测试的结果在方框1中的准确性为77.44%,在方框2中的准确性为97.88%,在方框3中的准确性为77.8%。在相同模型上进行的移动机器人测试显示,在模糊上的距离输入值增大后,精度会提高。未来的研究可以使用机器学习方法。

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