Trajectory Estimation of Remote Operated Vehicle Using Particle Filter for Circular Motion

The development of marine survey technology is increasing quite rapidly and has an impact on time efficiency, costs, better data resolution, and the risk of personnel loss. With the advances in technology, the function of divers in investigative surveys can be replaced by Remotely Operated Vehicles (ROV). ROV is an unmanned underwater vehicle equipped with various systems integrated into it such as an underwater positioning system, video camera, and others depending on the needs and objectives of the survey. The ROV is controlled and steered by computers on board, the support vessel, with six degrees of freedom. This paper focuses on the navigation system on an ROV through a trajectory estimation method of a 6-DOF ROV nonlinear model, especially for turning motion. The study used a fairly reliable estimation method, that is, Particle Filter. The simulation results showed that the Particle Filter method has an accuracy of more than 98% for both circular trajectories without diving and circular trajectories with diving.