An artificial neural network approach to the problem of wireless sensors network localization

Undelayed 3D RO-SLAM based on Gaussian-mixture and reduced spherical parametrization

“…This paper presented a general solution for the 3D Rangeonly SLAM using a reduced spherical parametrization for the position of map features allowing to reduce the required 1 Complete results are shown in the video attached to this paper which can also be found in the URL: http://grvc.us.es/staff/felramfab/iros2013/video.avi computational load. The solution is based on a centralized EKF-SLAM which includes the position of the robot and the position of all range sensors (map features) which allows the integration of sensor to sensor measurements and not only between robot to sensor keeping the correlation between each pair of sensors and the correlation between sensor to robot.…”

“…Thus, [1] presents a localization solution where a neural network is used to learn the observation model of a set of fixed radio emitters in order to get the location of a mobile ground robot by learning the signal power associated to each location in a map (fingerprinting methods). The inputs of this neural network are the distance measurements of each sensor and the output is the 2D location of the mobile robot.…”

Soft computing-based localizations in wireless sensor networks

“…In addition to the traditional centroid, location approximation in WSNs can also be derived from soft computing techniques [28][29][30][31][32][33][34][35][36][37][38][39][40][41]. In general, soft computing techniques are used to resolve the problem with an uncertainty solver as well as a non-linear solver [17,18].…”

“…However, since in the research, the focus is on soft computing based approaches, some of the intelligent routing protocols [21,24,25,[28][29][30][31][32][33][34][35][36][37][38]43,48,56] are preferred for probable seamless integration for WSN applications, such as swarm based routing protocols [24], fuzzy multi-objective routing (FMO), genetic algorithm based energy-efficient clustering protocol (GA-EECP), and sensor intelligence routing (SIR-NN based routing) [25]. Note that these further investigations are for future work.…”

WSNs Performance Evaluation Using Non-equilibrium Statistical Mechanics Method

“…In distinct application environment, the network performance of WSNS shown are very distinct, we must put forward an overall analysis and corresponding evaluation method for WSNs performance index of the corresponding. Gholami, N. Cai emphasized the temporal performance dynamics of wireless links and provided important findings about such phenomenon [19]. Okdem, Selcuk had proposed evaluating WSNs performance from a global or overall angle [20]; Bhuyan, Bhaskar presented a comprehensive study to quantify and characterize link quality [21].…”