Time-Optimal Trajectory Planning and Model Predictive Control of Morphing Quadrotors
Qiuyu Wang, Na Zhao, Chaojun Qin, Xiyu Ke, Yudong Luo, Yantao Shen
AI summary
Problem
Conventional quadrotors lack adaptability in cluttered environments, while existing morphing quadrotor control frameworks struggle with aggressive morphing-induced dynamics and neglect time-optimal planning, leading to excessive energy consumption and reduced mission time.
Approach
The authors propose a time-optimal trajectory generator that dynamically adjusts arm lengths to minimize flight time, coupled with a structure-adaptive dual-loop MPC controller that synchronously tracks position and regulates attitude and morphing dynamics in real time.
Key results
- First time-optimal path planning method explicitly accounting for morphing arm-length dynamics
- Full-DOF dual-loop MPC controller handling real-time morphing-induced dynamic disturbances
- Experimental validation demonstrating high-precision tracking and robust dynamic response in confined spaces
- Multi-stage radius-transition trajectory generation proving efficient structural adaptation during flight
Why it matters
Enables longer, more efficient autonomous missions for morphing drones in cluttered or restricted spaces, advancing their practical deployment in inspection, logistics, and rescue operations.
Abstract
Morphing quadrotors offer enhanced maneuver- ability and adaptability in confined spaces, while their struc- tural variations pose challenges to trajectory planning and control. This paper presents a time-optimal trajectory planning and model predictive control framework for the morphing quadrotor. The trajectory generator computes time-optimal trajectories by dynamically adjusting arm lengths, allowing the quadrotor to traverse waypoints as quickly as possible while satisfying constraints. The generated trajectory is then fed into the designed dual-loop model predictive control architecture to achieve autonomous flight, in which the outer loop tracks the desired trajectory and the inner loop synchronously regulates attitude and the morphing quadrotor’s arm length. Experi- mental validation demonstrates that the proposed framework achieves high-precision trajectory tracking, robust dynamic response, and superior adaptability in confined environments.