Trajectory Generation and Tracking Control for Aggressive Tail-Sitter Flights
Guozheng Lu, Yixi Cai, Nan Chen, Fanze Kong, Yunfan Ren, Fu Zhang

TL;DR
This paper presents a comprehensive framework for trajectory generation and high-precision tracking control of tail-sitter UAVs, leveraging differential flatness and aerodynamic models for agile, aggressive flight in complex environments.
Contribution
It introduces a novel differential flatness property for tail-sitters with aerodynamic models, enabling advanced trajectory planning and control in the entire flight envelope.
Findings
Successful real-world tests including narrow window flights and aerobatic maneuvers.
High-accuracy trajectory tracking achieved with the proposed MPC approach.
Demonstrated robustness in indoor and outdoor environments with speeds up to 20m/s.
Abstract
We address the theoretical and practical problems related to the trajectory generation and tracking control of tail-sitter UAVs. Theoretically, we focus on the differential flatness property with full exploitation of actual UAV aerodynamic models, which lays a foundation for generating dynamically feasible trajectory and achieving high-performance tracking control. We have found that a tail-sitter is differentially flat with accurate aerodynamic models within the entire flight envelope, by specifying coordinate flight condition and choosing the vehicle position as the flat output. This fundamental property allows us to fully exploit the high-fidelity aerodynamic models in the trajectory planning and tracking control to achieve accurate tail-sitter flights. Particularly, an optimization-based trajectory planner for tail-sitters is proposed to design high-quality, smooth trajectories with…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Aerospace and Aviation Technology · Adaptive Control of Nonlinear Systems
