Development of an unmanned robot based on artificial intelligence

DOI: 10.31673/2409-7292.2024.030006

Abstract

The development of unmanned robots based on artificial intelligence (AI) is an extremely relevant topic in today's world, as AI is used to create a variety of autonomous systems capable of performing tasks without direct human intervention. One of the key aspects of such systems is the robot's ability to capture targets with the help of AI. The development of an AI-based unmanned robot for target capture includes several main stages. First, the theoretical foundations of AI and machine learning are studied, in particular image processing and object recognition algorithms. This phase involves analyzing the scientific literature, patents and technical documentation to understand the current state of affairs in the field of unmanned robots and to determine the most effective approaches to capture targets. This article is devoted to a detailed description of the development of an unmanned robot capable of autonomously capturing targets with the help of AI. After theoretical analysis, algorithms are developed for target detection and tracking using Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). Models are trained on large image datasets containing a variety of target variants. The drone's AI will work on the basis of Convolutional Neural Networks (CNN) for object recognition and Recurrent Neural Networks (RNN) for target tracking. The model will learn to recognize and capture objects using large data sets that include images of objects from different angles and lighting conditions. The software tools were analyzed, the architecture of the navigation system of the unmanned robot was developed, including the interaction of sensors, planning and control algorithms.

Keywords: unmanned robot, artificial intelligence, target capture, object recognition, machine learning, depth sensors, manipulator, capture trajectory, autonomous robotics, sensor data integration.