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

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 onli...

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Bibliographic Details
Published in:IEEE/ASME transactions on mechatronics 2024-06, Vol.29 (3), p.1985-1996
Main Authors: Lee, Changyu, Chung, Dongha, Kim, Jonghwi, Kim, Jinwhan
Format: Article
Language:English
Subjects:
Acceleration
Autonomous navigation
Boats
Collision avoidance
Heuristic algorithms
Irrigation
marine robotics
Mathematical models
model predictive control (MPC)
Nonlinear control
Obstacle avoidance
Predictive control
System identification
Tracking control
Trajectory control
Trajectory planning
Vehicle dynamics
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Summary: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.
ISSN:1083-4435
1941-014X
DOI:10.1109/TMECH.2023.3312672