KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments
February 24, 2022 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Yanran Wang, James O'Keeffe, Qiuchen Qian, David Boyle
arXiv ID
2202.12419
Category
cs.RO: Robotics
Citations
12
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
Abstract
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 effects of 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 demonstrate that our system improves the accuracy of tracking in selected environments with unpredictable aerodynamic effects.
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