Visual Servo Control for Autonomous Drone Racing

@inproceedings{ICRA2024CQ,

title = {Time-Optimal Gate-Traversing Planner for Autonomous Drone Racing},

author = {Chao Qin* and Maxime S.J. Michet* and Jingxiang Chen* and Hugh H. -T. Liu},

year  = {2024},

date = {2024-01-31},

urldate = {2024-01-31},

booktitle = {2024 IEEE International Conference on Robotics and Automation (ICRA)},

publisher = {IEEE, Best Paper Award Finalist!},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{AIM2023CQ,

title = {Perception-Aware Image-Based Visual Servoing of Aggressive Quadrotor UAVs},

author = {Chao Qin* and Qiuyu Yu* and Shing Hei Helson Go* and Hugh H. -T. Liu},

url = {https://www.youtube.com/watch?v=X2-SMGD99oA},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {Advanced Intelligent Mechatronics (AIM)},

journal = {IEEE/ASME International Conference on Advanced Intelligent Mechatronics},

publisher = {IEEE},

abstract = {The maintenance of visual features within the sensor field of view (FOV) poses a significant challenge for underactuated aerial vehicles like quadrotors, especially during aggressive maneuvers. However, existing image-based visual servo control (IBVS) methods rely on strict target visibility assumptions or impose excessive constraints on the quadrotor's agility to meet this requirement. Furthermore, the effectiveness of the visibility constraint defined in prior works remains unverified in aggressive flight tests. To address these issues, we present a robust IBVS scheme for quadrotors to perform aggressive maneuvers while ensuring target visibility. Based on the nonlinear model predictive control (NMPC) framework, we propose a novel underactuation compensation scheme to eliminate the need for a virtual camera frame, which enables us to formulate the true target visibility constraint. We then introduce a quaternion-based representation of spherical visual features to handle the nonsmooth vector field problem on the 2-sphere and derive its corresponding image kinematics. We validate our method through three challenging visual servo tasks where agile maneuvers are desired: fast landing, aggressive long-distance flight, and dynamic object tracking. Extensive simulation and experiment show that our method consistently achieves a target-visible rate of 100% in all image frames, even under a maximum pitch of 21.04$^circ$. The results validate the effectiveness of our visibility constraint under large robot rotations and underscore its importance in enabling robust and aggressive flights.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}