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Real-time Optimal Planning and Model Predictive Control of a Multi-rotor with a Suspended Load

Cited 5 time in Web of Science Cited 7 time in Scopus
Authors

Son, Clark Youngdong; Jang, Dohyun; Seo, Hoseong; Kim, Taewan; Lee, HyeonBeom; Kim, H. Jin

Issue Date
2019-05
Publisher
IEEE
Citation
2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), pp.5665-5671
Abstract
This paper presents planning and control algorithms for a multi-rotor with a suspended load. The suspended load cannot be controlled easily by the multi-rotor due to severe dynamic coupling between them. Difficulties are exacerbated by under-actuated, highly nonlinear nature of multi-rotor dynamics. Although many studies have been proposed to plan trajectories and control this system, there exist only a few reports on real-time trajectory generation. With this in mind, we propose a planning method which is capable of generating collision-free trajectories real-time and applicable to a high-dimensional nonlinear system. Using a differential flatness property, the system can be linearized entirely with elaborately chosen flat outputs. Convexification of non-convex constraints is carried out, and concave obstacle-avoidance constraints are converted to convex ones. After that, a convex optimization problem is solved to generate an optimal trajectory, but semi-feasible trajectory which considers only some parts of the initial state. We apply model predictive control with a sequential linear quadratic solver to compute a feasible collision-free trajectory and to control the system. Performance of the algorithm is validated by flight experiment.
ISSN
1050-4729
URI
https://hdl.handle.net/10371/187144
DOI
https://doi.org/10.1109/ICRA.2019.8793674
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