Imperial College London
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MrYanranWang

Faculty of Engineering, Dyson School of Design Engineering

Research Postgraduate
 
 
 
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Contact

 

yanran.wang20 CV

 
 
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Location

 

Dyson BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Wang:2022:10.1109/ICRA46639.2022.9812352,
author = {Wang, Y and O'Keeffe, J and Qian, Q and Boyle, D},
doi = {10.1109/ICRA46639.2022.9812352},
pages = {11036--11043},
title = {KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments},
url = {http://dx.doi.org/10.1109/ICRA46639.2022.9812352},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Unmapped areas and aerodynamic disturbances render autonomous navigation with quadrotors extremely challenging. To fly safely and efficiently, trajectory planners and trackers must be able to navigate unknown environments with unpredictable aerodynamic effects in real-time. When encountering aerodynamic effects such as strong winds, most current approaches to quadrotor trajectory planning and tracking will not attempt to deviate from a determined plan, even if it is risky, in the hope that any aerodynamic disturbances can be resisted by a robust controller. This paper presents a novel systematic trajectory planning and tracking framework for autonomous quadrotors. We propose a Kinodynamic Jump Space Search (Kino-JSS) to generate a safe and efficient route in unknown environments with aerodynamic disturbances. A real-time Gaussian Process is employed to model the errors caused by aerodynamic disturbances, which we then integrate with a Model Predictive Controller to achieve efficient and accurate trajectory optimization and tracking. We demonstrate our system to improve the efficiency of trajectory generation in unknown environments by up to 75% in the cases tested, compared with recent state-of-the-art. We also show that our system improves the accuracy of tracking in selected environments with unpredictable aerodynamic effects. Our implementation is available in an open source package11https://github.com/Alex-yanranwang/Imperial-KinoJGM.
AU  - Wang,Y
AU  - O'Keeffe,J
AU  - Qian,Q
AU  - Boyle,D
DO  - 10.1109/ICRA46639.2022.9812352
EP  - 11043
PY  - 2022///
SN  - 1050-4729
SP  - 11036
TI  - KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments
UR  - http://dx.doi.org/10.1109/ICRA46639.2022.9812352
ER  -
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