Collision avoidance planning for unmanned surface vehicle based on eccentric expansion. (7th June 2019)

• Record Type: Journal Article
• Authors: Song, Lifei; Chen, Zhuo; Dong, Zaopeng; Xiang, Zuquan; Mao, Yunsheng; Su, Yiran; Hu, Kai
• Is Part Of: International journal of advanced robotic systems. Volume 16:Number 3(2019:May/Jun.)
• Publication Date: 2019-06-07
• Subjects: Unmanned surface vehicle -- eccentric expansion -- obstacle avoidance -- velocity obstacle method -- convention on the International Regulations for Preventing Collisions at Sea -- path planning and navigation; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881419851945
• Languages: English
• ISSNs: 1729-8806

Abstract

The International Regulations for Preventing Collisions at Sea (COLREGS) specify certain navigation rules for ships at risk for collision. Theoretically, the safety of unmanned surface vehicles and traffic boats would be guaranteed when they comply with the COLREGS. However, if traffic boats do not comply with the demands of the convention, thereby increasing the danger level, then adhering to the COLREGS may be dangerous for the unmanned surface vehicle. In this article, a dynamic obstacle avoidance algorithm for unmanned surface vehicles based on eccentric expansion was developed. This algorithm is used to solve the possible failure of collision avoidance when the unmanned surface vehicle invariably obeys the COLREGS during the avoidance process. An obstacle avoidance model based on the velocity obstacle method was established. Thereafter, an eccentric expansion operation on traffic boats was proposed to ensure a reasonable balance between safety and the rules of COLREGS. The expansion parameters were set according to the rules of COLREGS and the risk level of collision. Then, the collision avoidance parameters were calculated based on the aforementioned motion model. With the use of MATLAB and Unity software, a semi-physical simulation platform was established to perform the avoidance simulation experiment under different situations. Results show the validity, reliability and intellectuality of the algorithm. This research can be used for intelligent collision avoidance of unmanned surface vehicle and other automatic driving ships.