Evolving Collaborative Differential Evolution for Dynamic Multi-objective UAV Path Planning - Xu, Renjie; Huang, Zhaoke; Wang, Chenwei; Yan, Hong (IEEE transactions on vehicular technology, 2025)
The application of unmanned aerial vehicles (UAVs) in urban environments introduces complex challenges to path planning due to dynamic targets, changing environmental con ditions, and stringent safety requirements. To address these issues, this paper proposes an Evolving Collaborative Differential Evolution (ECDE) algorithm specifically designed for dynamic multi-objective UAV path planning. ECDE integrates an adaptive hyperparameter tuning mechanism, a robust change detection strategy, and a collaborative learning strategy to effectively balance multiple conflicting objectives, such as minimizing path length, energy consumption, noise pollution, and collision risk. Comprehensive experimental evaluations are conducted under various scenarios, including static environments, dynamic targets, and risk-adaptive urban navigation. The results demonstrate that ECDE consistently achieves superior global optimization performance and adaptability compared to state-of-the-art multi objective optimization methods, thereby significantly enhancing UAV operational effectiveness in complex, real-world urban scenarios.