Robust UAV Path Planning with Obstacle Avoidance for Emergency Rescue

TL;DR

A novel artificial potential field algorithm coupled with simulated annealing (APF-SA) is proposed to tackle the robust path planning problem for UAVs with obstacle avoidance, demonstrating the effectiveness of APFSA.

Abstract

The unmanned aerial vehicles (UAVs) are efficient tools for diverse tasks such as electronic reconnaissance, agricultural operations and disaster relief. In the complex three-dimensional (3D) environments, the path planning with obstacle avoidance for UAVs is a significant issue for security assurance. In this paper, we construct a comprehensive 3D scenario with obstacles and no-fly zones for dynamic UAV trajectory. Moreover, a novel artificial potential field algorithm coupled with simulated annealing (APF-SA) is proposed to tackle the robust path planning problem. APF-SA modifies the attractive and repulsive potential functions and leverages simulated annealing to escape local minimum and converge to globally optimal solutions. Simulation results demonstrate that the effectiveness of APF-SA, enabling efficient autonomous path planning for UAVs with obstacle avoidance.

Figures (8)

• Figure 1: Obstacle avoidance trajectory scenario for UAV in 3D environment.
• Figure 2: Path planning model for UAV.
• Figure 3: APF principle.
• Figure 4: Comparison of attractive force function original v.s. modified.
• Figure 5: Performance of local minimum with different methods.