ANN design model to recognize the direction of Multi-Robot AGV

Aan Eko Setiawan and Angga Rusdinar and Rina Mardiati and Eki Ahmad Zaki Hamidi ANN design model to recognize the direction of Multi-Robot AGV. In: UNSPECIFIED.

Preview

Text ANN Design Model to Recognize The Direction of Multi-Robot AGV.pdf Download (1MB) | Preview

Abstract

Automatic Guided Vehicle (AVG) Robot is a kind of mobile robot. This robot serves to transport goods from one place to a certain place. One type of robot that is currently being developed and researched is the multi robot. This robot is more focused in terms of communication between robots, so that the robots will not collide with each other. In its implementation, multi- robots differentiate from each other by communicating using camera sensors, so that image processing will be carried out. In this study, an Artificial Neural Network (ANN) model will be implemented which can differentiate between two robots. There are six input which are R1L, R1SR, R1SL, R2Ls, R2SR and R2 SL. The number of data sets entered is 300 data which is divided into 225 train data and 75 test data. The activation used are RelU and Softmax. The optimizer used is the Adam optimizer with a learning rate of 0.003, epoch used 50 with a batch size of 25. The result shows that the accuracy of the ANN model was 96%.

Actions (login required)

View Item