An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments

• DOI: 10.3390/app8020193
• Publication Date: 2018-01-29T12:46:20Z
• Authors: Xiaojie Sun; Guofeng Wang; Yunsheng Fan; Dongdong Mu; Bingbing Qiu
• Keywords: Unmanned surface vehicle; Obstacle avoidance

In recent years, unmanned surface vehicles (USVs) have received notable attention because of their many advantages in civilian and military applications. To improve the autonomy USVs, this paper describes a complete automatic navigation system (ANS) with path planning subsystem (PPS) collision avoidance (CAS). The PPS based on dynamic domain tunable fast marching square (DTFMS) method is able to build an environment model from real electronic chart, where both static obstacles are well represented. By adjusting S t u r i o n , generated can be changed according requirements for security length. Then it used as guidance trajectory CAS through target point. CAS, finite control set predictive (FCS-MPC) theory, algorithm developed track avoid three-degree freedom (DOF) planar motion USV. Its point evaluation come planned environmental PPS. Moreover, prediction guide changes vessel itself. Finally, has been tested validated using situations three types encounters realistic sea environment.