This paper presents an online coverage method for the exploration of unknown oceanic terrains using multiple autonomous underwater vehicles (AUVs). Working from the concept of planar algorithm developed by Hert, this study attempts to develop an improved method. Instead of theoretical research, it focuses on the practical aspects of exploration by considering the equations of motion for AUVs that are actually used in oceanic exploration as well as on the characteristics of complex oceanic topography and other realistic variables, such as sea current. These elements are used to calculate cross track error (CTE) and path width for AUV movement. The validity of the improved algorithm for terrain coverage is first verified mathematically and then by a simulation of the real underwater environment that analyzes the path length and time taken for the coverage as well as the missed areas, which is the key element of efficiency. In order to apply the improved method to the multi-AUV operation, each AUV was assigned a covering or a scanning role by means of a dynamic role-changing mechanism. The results showed that the multi-AUV operation has an advantage over a single-AUV operation in many ways. The method proposed in this study will be useful not only for commercial applications but also for mine counter-measures (MCMs) and rapid environmental assessments (REAs) as part of naval military operations as well. We also believe that it will be ideal for use in variable oceanic environment, particularly in shallow water terrains. For the purposes of this study, we assume that the communication between AUVs is problem-free.

In this paper, we propose a new localization algorithm based on a hybrid trilateration algorithm for obtaining an accurate position of a robot in intelligent space. The proposed algorithm is also able to estimate a position of the moving robot by using the extended Kalman filter, taking into consideration time synchronization and velocity of the robot. For realizing the localization system, we employ several smart sensors as beacons on the ceiling in intelligent space and as a listener attached to the robot. Finally, simulation results show the feasibility and effectiveness of the proposed localization algorithm compared with existing trilateration algorithms.

This article summarizes a research topic which discusses one of the most common problems in multiple micro-robots' navigation, namely congestion avoidance. This situation occurs when troops of micro-robots moving in different directions meet each other at a common area causing congestion situations. To avoid this risky statewhich can create an inextricable scenario -firstly, we established a local and a global communication network that manages the robots' displacement through formation control. This warns each of them of the existence of a risk of congestion and manages the choice of the priority group, which is a new concept that we introduce in order to deal with this kind of congestion conflict. Secondly, we consider a new algorithm based on chaotic equations and inspired by the behaviour of schools of fish, which solves the congestion problem by creating a bifurcation of the troop's configuration and enables the proper avoidance of the conflict exhibited by congestion.

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