A multi-parametric path planning framework utilizing airspace visibility graphs for urban battlefield environments

Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors, such as static and dynamic obstructions as well as risks of exposure to enemy detection, which threaten flight safety and mission success. Traditional path planning methods typically depend solely on the distribution of static obstacles to generate collision-free paths, without accounting for constraints imposed by enemy detection and strike capabilities. Such a simplified approach can yield safety-compromising routes in highly complex urban airspace. To address these limitations, this study proposes a multi-parameter path planning method based on reachable airspace visibility graphs, which integrates UAV performance constraints, environmental limitations, and exposure risks. An innovative heuristic algorithm is developed to balance operational safety and efficiency by both exposure risks and path length. In the case study set in a typical mixed-use urban area, analysis of airspace visibility graphs reveals significant variations in exposure risk at different regions and altitudes due to building encroachments. Path optimization results indicate that the method can effectively generate covert and efficient flight paths by dynamically adjusting the exposure index, which represents the likelihood of enemy detection, and the path length, which corresponds to mission execution time.