Abstract
Pipe robot is a robot capable of moving inside the pipe. The function of the pipe robot is to monitor pipe defects. The pipe robot is designed to move steadily in the center position inside the pipe. HCSR-04 distance sensor required input to give distance value to the microcontroller so that robot keep running stable and balance, for movement of the robot using DC motor. This robot is made with the aim to move autonomously following the pipeline in detecting pipe cracks. Programming on this robot using Artificial Neural Network algorithm with the Backpropogation method of network structure, consist of 3 input layer, 3 output layer, and 20 hidden layers. Conducted experiments on inputs, hidden layers, and outputs with varying amounts to obtain robust network structure of efficient and precise movement of robots in detecting pipe cracks. The result of movement of the robot in the application of Artificial Neural Network algorithm with Backpropagation method is able to move well and more stable. In this case, it uses 2 ultrasonic sensors and 2 motor outputs. The average robot speed movement is 10 cm/sec.
Highlights
Robot comes from the language of robko Cheko which means workers who are tireless or bored
Artificial neural networks backpropagation consists of many layers, namely: 1) input layer, consists of neurons or input units, from input 1 to input unit n; 2) hidden layer, consists of hidden units ranging from hidden units 1 to hidden units p; 3) output layer, consists of units of output starting from the output unit 1 to the output unit m
The symbols n, p, m are each arbitrary integer numbers according to the artificial neural network artifacts (Widiastuti, 2014)
Summary
Robot comes from the language of robko Cheko which means workers who are tireless or bored. Controlled (usually not linear) on the network input to derobots can use sensors as distance detectors for termine its output signal (Widiastuti, 2014). The detection of boundaries in the pipe avoid if there are obstacles, such as a wall. The space and the positioning of the positions are obstacle avoider robot requires at least three two important and fundamental roles of naviga- sensors to detect obstacles ie front, right and tion. Robots need a lot of sensors position estimation is required in order for the due to better detection of barrier. This is due to robot to get the position to fit its environment the limited angle of sensor jets (usually around (Crawley, 1989). The assumptions that: 1) Information processing occurs on elements called neurons; 2)
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