Cooperative Trajectory Planning and Formation Tracking Control for Risk-Averse Heterogeneous Aerial Vehicles

Heterogeneous autonomous small aerial vehicles are gradually becoming a major component of the low-altitude economy. This study addresses the problem of cooperative trajectory planning and optimization for heterogeneous aerial vehicle systems operating under cooperative control frameworks. Focusing on cooperation between fixed-wing and quadrotor platforms, a trajectory generation method is developed based on quaternionrepresented Pythagorean hodograph curves, which explicitly accounts for the distinct dynamic constraints inherent to each vehicle type. To enhance robustness under uncertainty, a risk-averse optimization framework is introduced to model constraints on the tracking state and control variables of aerial vehicles. A dynamic risk measure model is proposed to quantitatively capture the uncertainty and constraint violations associated with the dynamics of heterogeneous systems, serving as a foundation for risk-aware trajectory optimization and control. These constraints are integrated into a model predictive control architecture to achieve optimal and reliable cooperation. The effectiveness and practical applicability of the proposed approach are validated through a series of experiments involving a five-agent heterogeneous aerial vehicle formation.