Scholarlink

<p>This study introduces an optimal UAV collision control approach that combines the Improved Rapidly-exploring Random Tree Star (RRT*) algorithm for global path planning with the Dynamic Window Approach (DWA) for real-time adjustments. This hybrid approach allows the UAV to dynamically switch between long-range planning for static obstacles and precise trajectory refinement in dynamic environments. By utilizing LiDAR and ultrasonic sensors, the model autonomously adapts flight paths based on nearby threats. Experimental results demonstrate faster response times and enhanced energy efficiency compared to standalone implementations of RRT* and DWA, validating its effectiveness in collision avoidance and traffic management, thereby facilitating the safe integration of UAVs into urban airspace.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrated RRT* and Dynamic Window Approach for UAV Obstacle Control

  • 期刊论文

  • 发表日期：

    2025年5月20日

查看全文
  • Kalp Jain,
  • Aditya Kashyap

摘要

This study introduces an optimal UAV collision control approach that combines the Improved Rapidly-exploring Random Tree Star (RRT*) algorithm for global path planning with the Dynamic Window Approach (DWA) for real-time adjustments. This hybrid approach allows the UAV to dynamically switch between long-range planning for static obstacles and precise trajectory refinement in dynamic environments. By utilizing LiDAR and ultrasonic sensors, the model autonomously adapts flight paths based on nearby threats. Experimental results demonstrate faster response times and enhanced energy efficiency compared to standalone implementations of RRT* and DWA, validating its effectiveness in collision avoidance and traffic management, thereby facilitating the safe integration of UAVs into urban airspace.