Minimum Snap Trajectory Planning and Augmented MPC for Morphing Quadrotor Navigation in Confined Spaces

Existing studies rarely investigate the dynamic morphology factor on motion planning and control, which is crucial for morphing quadrotors to achieve autonomous flight. Therefore, this paper studies the collaborative optimization of trajectory generation and flight control for the morphing quadrotor with real-time adjustable arms. In the motion planning layer, an objective function that combines position and morphology is constructed by embedding variable arm length as a decision variable into the conventional minimum snap trajectory generation framework. The generated trajectory not only satisfies the speed and acceleration constraints, but also smoothly passes through the narrow spaces that are difficult for traditional quadrotors to traverse. In the control layer, a constrained augmented model predictive control based on the dynamics of the morphing quadrotors is proposed to follow the generated trajectory with an embedded integrator, which is added by exploiting the differential flat variables to improve the tracking performance. In the numerical studies, a scenario with a corridor was considered to demonstrate the effectiveness of the proposed control strategy to achieve optimal trajectory under multiple constraints.