Autonomous patrol vessels are state border patrol vessels equipped with cameras and image processing capabilities to detect objects around them. This prototype of ship can recognize a detected object; it used an image classification method called Convolutional Neural Network (CNN). So, it will minimize the occurrence of accidents on patrol boats. Input image in the form of RGB will experience feature extraction using a convolution layer. In the classification layer there is an artificial neural network with backpropagation to classify objects against a predetermined dataset. The detection value of the obtained vessel is operated by a predetermined actuator. In the final classification results the object recognition in the form of ships have a quite high accuracy. The average accuracy value is 96.59 percent with a sufficient light condition and RGB image input is taken in real-time.
In this research Trigonometry Technique was implemented to predict the ball movement direction for Wheeled Soccer Robot Goalkeeper. The performance of goalkeeper robot in Wheeled Soccer Robot Contest is very important. The crucial problem with goalkeeper robot is the delay in ball detection by the camera because the results of the camera images captured are always slower than the pictures that have been captured. This causes the robot's response to blocking the opponent's kick ball being late. Trigonometry Technique is one technique that can be used to predict the direction of the ball movement based on trigonometry mathematical formulas. The input data used is the location of the last ball position (x–last ball and y-last ball) and the location of the current ball position (x-current ball and y-current ball). The outputs are the prediction of the next ball location (x-predict ball and y-predict ball) and the prediction of ball movement direction prediction. The results are the goalkeeper's robot successfully predicts the opponent's kick direction with 90% accuracy and can predict the location of the next ball very well. By implementing this method, it is expected to optimize the performance of the goalkeeper robot in saving the goal.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.