Implementation Of Android-Based Fish Detection & Recognition System Using Convolutional Neural Network Method

Today the development of robots has increased a lot. Over time the robot can used as a medium of learning and education. The maze mapping system can be used as educational media in robotics. In this study, the idea was obtained to design a robot moving objects that are able to move on a flat striped plane like a line tracer robot. Robot it adopts a maze mapping system to find the fastest path in moving objects. These objects are in the form of mini objects that have been given a color consisting of red, yellow, green, and blue. The four colors are used as a reference for the robot to detect objects based on the color that will be moved from the object detection start point to the available finish point. The method to be used on the robot is A*. The A* algorithm is able to find the fastest route on the path traversed by the robot, by adding up the actual distance with the estimated distance thus making it optimal in the search for the route. The microcontroller used on This robot is an Arduino Due which functions to enter data from the results of sensor readings is on the robots. The sensors consist of an infrared module that functions as a detector line and TCS34725 color sensor to detect the object to be moved. This wheeled robot using a DC motor with a voltage of 12V to drive the two wheels. Than 10 times experiment to determine the fastest path with 1 type of color, obtained success with 70%. The results of this study can be used as a comparison material for the A* method with the A* method another fastest path search.