Real-Time Obstacle Avoidance Algorithms for Unmanned Aerial and Ground Vehicles

TL;DR

This paper introduces real-time obstacle avoidance algorithms for UAVs and UGVs, focusing on complex 3D environments like forest fires to enhance autonomous rescue operations.

Contribution

It develops novel 2D and 3D reactive navigation strategies and a unified control approach for coordinated UAV and UGV rescue missions in hazardous environments.

Findings

Effective 2D fusion navigation for dynamic environments

Collision-free 3D navigation in forest fire simulations

Validated control models through mathematical and simulation evidence

Abstract

The growing use of mobile robots in sectors such as automotive, agriculture, and rescue operations reflects progress in robotics and autonomy. In unmanned aerial vehicles (UAVs), most research emphasizes visual SLAM, sensor fusion, and path planning. However, applying UAVs to search and rescue missions in disaster zones remains underexplored, especially for autonomous navigation. This report develops methods for real-time and secure UAV maneuvering in complex 3D environments, crucial during forest fires. Building upon past research, it focuses on designing navigation algorithms for unfamiliar and hazardous environments, aiming to improve rescue efficiency and safety through UAV-based early warning and rapid response. The work unfolds in phases. First, a 2D fusion navigation strategy is explored, initially for mobile robots, enabling safe movement in dynamic settings. This sets the stage for advanced features such as adaptive obstacle handling and decision-making enhancements. Next, a novel 3D reactive navigation strategy is introduced for collision-free movement in forest fire simulations, addressing the unique challenges of UAV operations in such scenarios. Finally, the report proposes a unified control approach that integrates UAVs and unmanned ground vehicles (UGVs) for coordinated rescue missions in forest environments. Each phase presents challenges, proposes control models, and validates them with mathematical and simulation-based evidence. The study offers practical value and academic insights for improving the role of UAVs in natural disaster rescue operations.