Enhancing Land-Based Robotics Through the Development of Remotely Operated Vehicles for Military, Rescue and Industrial Applications

In recent years, there have been significant advancements in Remotely Operated Vehicles (ROVs), particularly in air and underwater applications. However, the progress in land-based ROVs has been slow, necessitating innovative approaches to address the existing challenges. This research paper presents a comprehensive analysis of the current state of land-based ROV technology, focusing on its limitations. A comprehensive solution is proposed, which combines well-established technology from the gaming industry, such as steering wheel controls and accelerators, with high-performance vehicle control systems to overcome these shortcomings. The suggested approach aims to enhance the control and precision of land-based ROVs using imitation learning techniques, thereby increasing operator safety during critical missions. The paper highlights the primary features and capabilities of the proposed model while underscoring its potential to revolutionize land-based robotic systems. The researchers aspire to advance the field of remote vehicles operating in challenging terrains by providing valuable insights derived from their study. The conclusions drawn from this research significantly impact the future development and utilization of land-based ROVs, paving the way for safer and more efficient operations across various sectors and applications.

I. Introduction

The development of ROVs for various uses, from underwater exploration to hazardous environment inspections, has attracted increasing interest in recent years. While substantial improvements have been made in ROVs, focusing on air and underwater capabilities, land-based ROVs have received much less attention. This research study proposes a novel approach that blends well-established gaming industry technology, like steering wheel controllers and accelerators, with military-grade vehicle control systems to close this gap. The suggested course aims to improve the control and precision of land-based ROVs while maintaining the safety of operators during crucial missions by merging these elements and using imitation learning techniques. The findings of this study could completely change the field of land-based robotic systems and open the door to improved remote vehicles operating in rugged terrain.