Method for Optimal Sensor Deployment on 3D Terrains Utilizing a Steady State Genetic Algorithm with a Guided Walk Mutation Operator Based on the Wavelet Transform

One of the most critical issues of Wireless Sensor Networks (WSNs) is the deployment of a limited number of sensors in order to achieve maximum coverage on a terrain. The optimal sensor deployment which enables one to minimize the consumed energy, communication time and manpower for the maintenance of the network has attracted interest with the increased number of studies conducted on the subject in the last decade. Most of the studies in the literature today are proposed for two dimensional (2D) surfaces; however, real world sensor deployments often arise on three dimensional (3D) environments. In this paper, a guided wavelet transform (WT) based deployment strategy (WTDS) for 3D terrains, in which the sensor movements are carried out within the mutation phase of the genetic algorithms (GAs) is proposed. The proposed algorithm aims to maximize the Quality of Coverage (QoC) of a WSN via deploying a limited number of sensors on a 3D surface by utilizing a probabilistic sensing model and the Bresenham's line of sight (LOS) algorithm. In addition, the method followed in this paper is novel to the literature and the performance of the proposed algorithm is compared with the Delaunay Triangulation (DT) method as well as a standard genetic algorithm based method and the results reveal that the proposed method is a more powerful and more successful method for sensor deployment on 3D terrains

A Novel Deployment Scheme Based on Three-Dimensional Coverage Model for Wireless Sensor Networks

Coverage pattern and deployment strategy are directly related to the optimum allocation of limited resources for wireless sensor networks, such as energy of nodes, communication bandwidth, and computing power, and quality improvement is largely determined by these for wireless sensor networks. A three-dimensional coverage pattern and deployment scheme are proposed in this paper. Firstly, by analyzing the regular polyhedron models in three-dimensional scene, a coverage pattern based on cuboids is proposed, and then relationship between coverage and sensor nodes’ radius is deduced; also the minimum number of sensor nodes to maintain network area’s full coverage is calculated. At last, sensor nodes are deployed according to the coverage pattern after the monitor area is subdivided into finite 3D grid. Experimental results show that, compared with traditional random method, sensor nodes number is reduced effectively while coverage rate of monitor area is ensured using our coverage pattern and deterministic deployment scheme

Automatic large-scale three dimensional modeling using cooperative multiple robots

Abstract3D modeling of real objects by a 3D laser scanner has become popular in many applications, such as reverse engineering of petrochemical plants, civil engineering and construction, and digital preservation of cultural properties. Despite the development of lightweight and high-speed laser scanners, the complicated measurement procedure and long measurement time are still heavy burdens for widespread use of laser scanning. To solve these problems, a robotic 3D scanning system using multiple robots has been proposed. This system, named CPS-SLAM, consists of a parent robot with a 3D laser scanner and child robots with target markers. A large-scale 3D model is acquired by an on-board 3D laser scanner on the parent robot from several positions determined precisely by a localization technique, named the Cooperative Positioning System (CPS), that uses multiple robots. Therefore, this system can build a 3D model without complicated post-processing procedures such as ICP. In addition, this system is an open-loop SLAM system and a very precise 3D model can be obtained without closed loops. This paper proposes an automatic planning technique for a laser measurement by using CPS-SLAM. Planning a proper scanning strategy depending on a target structure makes it possible to perform laser scanning efficiently and accurately even for a large-scale and complex environment. The proposed technique plans an efficient scanning strategy automatically by taking account of several criteria, such as visibility between robots, error accumulation, and efficient traveling. We conducted computer simulations and outdoor experiments to verify the performance of the proposed technique

Positioning and Utilizing Sensors on a 3-D Terrain Part I-Theory and Modeling

Positioning multiple sensors for acquisition of a given environment is one of the fundamental research areas in various fields, such as military scouting, computer vision, and robotics. In this paper, we propose a new model for the problem of sensor deployment. Deploying and configuring a set of given sensors on a synthetically generated 3-D terrain have multiple objectives on conflicting attributes: maximizing the visibility of the given terrain, maximizing the stealth of the sensors, and minimizing the cost of the sensors used. Since they are utility-independent, these complementary and conflicting objectives are modeled by a multiplicative total utility function, based on multiattribute utility theory. The total utility function proposed in this paper can also be adapted for various military scouting missions with different characteristics