Establishing Design Routines for Efficient Control of Automated Robots

TL;DR

This paper presents methodologies for integrating AI into robotic systems to improve control routines, human-robot interaction, and real-time performance, with a focus on industrial and research applications.

Contribution

It introduces new control routines, digital image processing methods, and a universal Arduino-based robotic system with GPS and memory algorithms.

Findings

Enhanced robotic control routines tested in real-time environments

Development of a universal Arduino-based robotic system

Improved efficiency and safety features for industrial robots

Abstract

With continual advancements in technology, efforts to develop robots simulating human behavior have intensified. Cognitive robotics, combined with artificial intelligence (AI), has proven effective in surveying and research analysis. However, despite progress, human intervention remains necessary, and incorporating AI into robotic systems continues to pose challenges. This paper explores methodologies to integrate AI into robotic designs, aiming to enhance human-robot interactions. Several approaches are proposed to improve robotic performance, including routines for efficient control in varied environments and the incorporation of digital image processing for enhanced line-of-sight capabilities. A key contribution of this work is testing robotic systems in real-time environments to assess efficiency relative to existing models. Additionally, the paper introduces a robotic system with universal control capabilities, suitable for industrial applications, developed and programmed on the Arduino platform. Features such as GPS control for safe operations and progressive memory algorithms for efficient memory management are presented, offering advancements in both industrial and research applications.