Nonlinear Model Predictive Control With Obstacle Avoidance Constraints for Autonomous Navigation in a Canal Environment

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In this article, we describe the development process of autonomous navigation capabilities of a small cruise boat operating in a canal environment and present the results of a field experiment conducted in the Pohang Canal, South Korea. Nonlinear model predictive control (NMPC) was used for the online trajectory planning and tracking control of the cruise boat in a narrow passage in the canal. To consider the nonlinear characteristics of boat dynamics, system identification was performed using experimental data from various test maneuvers, such as acceleration-deceleration and zigzag trials. To efficiently represent the obstacle structures in the canal environment, we parameterized the canal walls as line segments with point cloud data, captured by an onboard LiDAR sensor, and considered them as constraints for obstacle avoidance. The proposed method was implemented in a single NMPC layer, and its real-world performance was verified through experimental runs in the Pohang Canal.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2024-06
Language
English
Article Type
Article
Citation

IEEE-ASME TRANSACTIONS ON MECHATRONICS, v.29, no.3, pp.1985 - 1996

ISSN
1083-4435
DOI
10.1109/TMECH.2023.3312672
URI
http://hdl.handle.net/10203/322651
Appears in Collection
ME-Journal Papers(저널논문)
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