Path Planning of Low Altitude UAV for Urban Combat
Jincai Wang, Junhua Hu, An Liu, Jiacheng Ma, Shuyi Wang, Xingyu He · 2024
Addressing the challenge of unmanned aerial vehicle (UAV) path planning in urban combat, we establish a three-dimensional urban space model using the grid mapping method and “0-1” assignment approach. We simplify this complex three-dimensional environment into a two-dimensional representation through the application of the tangent projection technique. An objective function encompassing altitude, turning angle, pitch angle, and flight distance is introduced, providing a comprehensive evaluation framework. Based on this model, an enhanced A-Star algorithm is presented to augment planning efficacy. This algorithm incorporates measures to enhance the safe distance around obstacles, dynamically adjusts the heuristic function's convergence mode, and smooths the planned path to align with the UAV's flight capabilities. Simulation results demonstrate that the improved A-Star algorithm achieves a superior balance between safety and minimal path length, while significantly enhancing the rapidity and smoothness of the planning process.