## 1 Introduction
Moreover, the deployment strategy in [24] does not assure that all coverage holes are removed after the deployment. In this paper, we consider a robot which can freely move in 3D underwater environments. Under the proposed deployment strategy, all robots are deployed so that no sensing holes exist in the workspace. Suppose that a coverage mission of the underwater network is done. In this case, we need to gather the robots, so that they can be deployed for coverage of another space. By controlling the buoyancy of each robot, we can easily make each robot move to the sea surface. Then, a ship can collect the robots easily. The references [25; 26] handled 3D coverage path planning (i.e., path planning process for enabling full coverage of a given 3D space by one or multiple robots). The goal of such planning is to provide nearly full coverage, minimizing the occurrence of visiting an identical area multiple times. However, the references [25; 26] did not address how to deploy autonomous sensors, so that the 3D workspace is continuously monitored by the deployed sensors. In our paper, we develop coverage control so that once the robots are located at their designated target positions, then the 3D workspace is continuously monitored by the deployed robots. In practice, a robot may not be identical to another robot. For instance, some robots may not move as fast as other robots, since their hardware systems are partially broken during their operations. Hence, we assume that every robot moves with a distinct speed. Moreover, a robot may have a distinct sensing range with another robot. Hence, this article assumes that every robot is heterogeneous, such that each robot can have a distinct sensing range while moving with a distinct speed. This article thus handles a scenario where heterogeneous robots are deployed in unknown underwater environments. Since obstacles can block the communication link between robots, each robot is controlled while maintaining the network connectivity in obstacle-rich environments. The proposed coverage methods work by moving a single robot at a time to spread out the 3D sensor network, until the 3D workspace is fully covered without sensing holes. The surface ships dropping robots can use GPS to localize themselves. However, GPS cannot be used for localization of a robot. This article assumes that a robot can calculate the relative location of its neighboring robot using local sonar sensors. In underwater environments, sonar sensors are preferred, since sonar signal can travel a longer distance, compared to electromagnetic wave [18]. The proposed coverage methods result in underwater sensor networks without sensing holes, while localizing all robots. As far as we know, this article is novel in enabling multiple heterogeneous robots to build underwater sensor networks in a 3D cluttered environment, while satisfying the following conditions:  
1. remove all sensing holes. 2. network connectivity is maintained. 3. localize all underwater robots. This paper further addresses how to handle the case where a robot is broken. Also, we address how to conjecture the number of robots required, considering the case where an obstacle inside the 3D workspace is unknown a priori. Utilizing MATLAB simulations, we demonstrate the effectiveness of the proposed coverage methods. The article is organized as follows: Section 2 introduces the preliminary information of this article. Section 3 introduces the 3D coverage methods utilizing multiple heterogeneous robots. Section 4 shows the MATLAB simulations of the proposed 3D coverage methods. Section 5 presents the discussion on the paper. Section 6 discusses conclusions.