Machine learning has been heavily researched and widely used in many disciplines.
However, achieving high accuracy requires a large amount of data that is sometimes …

As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …

We learn end-to-end point-to-point and pathfollowing navigation behaviors that avoid
moving obstacles. These policies receive noisy lidar observations and output robot linear …

This research is concerned with the problem of obstacle avoidance for the underactuated
unmanned marine vessel under unknown environmental disturbance. A concise deep …

This paper aims to solve the path following problem for an underactuated unmanned-
surface-vessel (USV) based on deep reinforcement learning (DRL). A smoothly-convergent …

In the field of unmanned surface vehicles, intelligent collision avoidance technology is
essential to ensure the safety of navigating. In this paper, the problem of avoiding moving …

Localization is a critical issue for many location-based applications in the Internet of
Underwater Things (IoUT). Nevertheless, the asynchronous time clock, stratification effect …

In this article, the underwater target tracking control problem of a biomimetic underwater
vehicle (BUV) is addressed. Since it is difficult to build an effective mathematic model of a …

In a complex underwater environment, finding a viable, collision-free path for an
autonomous underwater vehicle (AUV) is a challenging task. The purpose of this paper is to …

This paper focuses on online obstacle avoidance planning for unmanned underwater
vehicles. To improve the autonomous ability and intelligence of obstacle avoidance …