无人飞行与地面车辆实时避障算法
Real-Time Obstacle Avoidance Algorithms for Unmanned Aerial and Ground Vehicles
AI总结：
本报告针对灾害区域自主导航问题，开发了用于UAV在复杂3D环境中实时安全机动的2D与3D反应式导航策略，并提出UAV与UGV统一控制方法，以提升森林火灾等救援任务的效率与安全性。
摘要：
移动机器人在汽车、农业和救援行动等领域的日益广泛应用反映了机器人技术和自主性的进步。在无人飞行车辆（UAV）中，大多数研究强调视觉SLAM、传感器融合和路径规划。然而，将UAV应用于灾害区域的搜索和救援任务仍然研究不足，特别是在自主导航方面。本报告开发了在复杂3D环境中进行实时和安全UAV机动的方法，这在森林火灾期间至关重要。基于过去的研究，它专注于为陌生和危险环境设计导航算法，旨在通过基于UAV的预警和快速响应来提高救援效率和安全性。这项工作分阶段展开。首先，探索了2D融合导航策略，最初用于移动机器人，使其能够在动态环境中安全移动。这为自适应障碍物处理和决策增强等高级功能奠定了基础。接下来，引入了一种新颖的3D反应式导航策略，用于森林火灾模拟中的无碰撞移动，解决了UAV在此类场景中操作的独特挑战。最后，报告提出了一种统一控制方法，将UAV和无人地面车辆（UGV）集成在一起，用于森林环境中的协调救援任务。每个阶段都提出了挑战，提出了控制模型，并用数学和基于仿真的证据进行了验证。该研究为改善UAV在自然灾害救援行动中的作用提供了实用价值和学术见解。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
