Abstract
In recent years, with the development of unmanned platforms, unmanned surface vehicles (USV) are attracting more and more attention. Compared to ordinary ships, USV have a smaller volume and faster speed, so their collision avoidance system (CAS) should have better responsiveness and stability. The paper describes a method that is based on finite control set model predictive control (FCS-MPC). A finite control set is generated by more practical control commands: the thruster speed and propulsion angle of the USV. The method is conceptually and computationally simple and yet quite versatile, as it can account for the dynamics of the USV, steering and propulsion system. Based on the theory of FCS-MPC, a safe and fast CAS is proposed, and it is verified in different static and dynamic environments. The real environment model for collision avoidance is established by extracting the environment data from the electronic chart. The result shows that the method is effective and can control the USV to sail safely and quickly in complex real scenarios with multiple dynamic obstacles.
Highlights
As a device for monitoring the marine environment, protecting marine rights and modern military weapons, the unmanned surface vehicle (USV) has a wide range of application prospects and has become a hot research topic for intelligent ships [1]
The contributions of this paper are that, firstly, the theory of finite control set model predictive control (FCS-Model predictive control (MPC)) is introduced into the collision avoidance of the USV, and the combination of path planning and the control system is realized to improve the safety and rapidity of collision avoidance for the USV; secondly, combining the characteristics of USV and the theory of FCS-MPC, a safe and fast collision avoidance system (CAS) is proposed; thirdly, it is more practical as the output of CAS is the thruster speed and propulsion angle, instead of force and torque; the CAS is verified in different static and dynamic environments, and the real environment model of collision avoidance is established from the electronic chart
The dynamic obstacles are obtained by environmental awareness equipment, such as radar, etc., and the detection area is set to a circle with the USV as the center and a radius of 250 m
Summary
As a device for monitoring the marine environment, protecting marine rights and modern military weapons, the unmanned surface vehicle (USV) has a wide range of application prospects and has become a hot research topic for intelligent ships [1]. Model predictive control (MPC) is increasingly being applied to vehicle navigation problems [11,12] It has been combined with path planning to achieve online stability and robustness [13,14]. The contributions of this paper are that, firstly, the theory of FCS-MPC is introduced into the collision avoidance of the USV, and the combination of path planning and the control system is realized to improve the safety and rapidity of collision avoidance for the USV; secondly, combining the characteristics of USV and the theory of FCS-MPC, a safe and fast CAS is proposed; thirdly, it is more practical as the output of CAS is the thruster speed and propulsion angle, instead of force and torque; the CAS is verified in different static and dynamic environments, and the real environment model of collision avoidance is established from the electronic chart.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
