Nonlinear control strategies for UAV navigation in complex terrains: a constraint-based approach for robust obstacle avoidance and mission efficiency

Unmanned aerial vehicles (UAVs) have demonstrated significant potential for intelligent transportation systems across various domains, including transportation systems, rescue missions, and environmental monitoring. However, navigating complex terrains necessitates sophisticated control strategies capable of effectively managing dynamic obstacles and environmental uncertainties. This paper employs a constraint-based dynamic control model that integrates the Udwadia–Kalaba method to address nonlinear motion constraints related to path planning and autonomous collision avoidance in navigation transportation systems. A diffeomorphic transformation is utilized to map complex operational requirements laden with constraints into a cohesive framework that incorporates both environmental considerations and mission-specific safety boundaries. To further enhance UAV performance, we introduce constraint following error measure and collision avoidance constraint transformation which facilitate a balanced integration between task-oriented objectives and safety constraints. Additionally, this framework employs robust control techniques to ensure trajectory accuracy under varying initial conditions, thereby improving the adaptability and stability of UAV motion. Simulation results validate that the proposed control design significantly enhances UAV agility and reliability, highlighting its potential for safe, efficient, and robust operation in both complex terrains and navigation transportation systems.