Enhancing the Heuristic Function of Improved A* Algorithm for UAV Robotic Arm Path Planning Using Dynamic Pigeon-Inspired Optimization

In recent years, unmanned aerial vehicle (UAV) has seen a surge in applications across various domains, including surveillance, logistics, and emergency response, due to their agility and versatility. A notable advancement in this area is the integration of robotic arms with UAV, enhancing their operational capabilities. However, the complex dynamic interactions between UAV flight dynamics and robotic arm movements, especially in obstacle-laden environments, pose significant path planning challenges. A novel approach to optimize UAV robotic arm path planning by enhancing the heuristic function of the A* algorithm through a dynamic pigeon-inspired optimization (DPIO) method is introduced by this paper. Our approach significantly improves real-time performance and reduces the mechanical torque exerted on the UAV, thereby ensuring more stable and efficient navigation. Experimental results demonstrate the efficacy of our method, particularly in complex outdoor settings, highlighting its potential to extend UAV applicability in precision tasks under challenging conditions.