Intelligent navigation process for autonomous underwater vehicles (AUVs) using time-based fuzzy temporal reasoning

An intelligent real-time multi-vessel collision risk assessment system from VTS view point based on fuzzy inference system

“…The process consisted of three stages (phases): firstly, the system was preventing the officer about the risk; secondly, the safe route was chosen by the system; and finally, this better route was drawn on the screen. The collision algorithm, proposed by the researchers, included the step of selecting the reference points using lattice-like reference points and OZT, based on speed and route respectively (Anvar, 2003). However the best way to improve that system was to integrate an expert system into the decision process.…”

Automatic object detection and diagnosis for AUV operation using underwater imaging sonar

“…The operational complexity increases when the rover navigates in milky-water or operates within a deep-dark-ocean-environment where there is not much energy available to light up the environment. To deal with such circumstances, it is vital to upgrade the sensory module to support robot localization, obstacle avoidance, navigation [7] and environmental map building. To equip the AUV with appropriate sensing capability for navigation within an underwater environment, acoustic sensors are most commonly chosen above cameras and laser sensors.…”

An obstacle-avoidance technique for autonomous underwater vehicles based on BK-products of fuzzy relation

“…The real-time operation of this capability is the main requirement within the autonomous vehicle's control management system. Many approaches to the problem have been proposed in recent years [1,2,6,[19][20][21]23]. Additionally, the heuristic search technique for obstacle avoidance of AUVs using Bandler and Kohourt (BK)-products has already been presented in [16,17].…”