Range-only fuzzy Voronoi-enhanced localization of mobile robots in wireless sensor networks

Robotica ◽  
2011 ◽  
Vol 30 (7) ◽  
pp. 1063-1077 ◽  
Author(s):  
D. Herrero ◽  
H. Martínez

SUMMARYWireless Sensor Network (WSN) localization has shown a growing research interest, thanks to the expected proliferation of WSN applications. This work is focused on indoor localization of a mobile robot in a WSN using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. These measurements are affected by different sources of uncertainty that make them highly noisy and unreliable. The proposed approach makes use of fuzzy logic for modeling and dealing with such uncertain information. Besides, the position estimation is enhanced using a rough description of indoor environment. The experiments show that the proposed localization approach (i) is fault-tolerant, (ii) results feasible in low-density WSNs, and (iii) provides better position estimations than well-known localization methods when the position measurements are affected by high uncertainty.

2012 ◽  
Vol 241-244 ◽  
pp. 972-975 ◽  
Author(s):  
Pei Zhi Wen ◽  
Ting Ting Su ◽  
Li Fang Li

In order to improve the positioning accuracy and reduce the localization cost, a kind of PSO-based RFID indoor localization algorithm is proposed in this paper. The main idea of this algorithm contains the following two aspects. First, due to the influence of none line of sight and multipath transmission in indoor environment, we adopt Gaussian Smoothing Filter to process Received Signal Strength Indicator (RSSI) values, which can reduce the impact of environmental factors on the position estimation effectively. Second, Particle of Swarm Optimization (PSO) algorithm is introduced to obtain a better positioning result. By experimenting in different indoor environment, the results demonstrate that the proposed approach can not only improve the precision of indoor localization, but has a lower cost and better robustness when compared to VIRE approach.


Author(s):  
CHI-LU YANG ◽  
YEIM-KUAN CHANG ◽  
YU-TSO CHEN ◽  
CHIH-PING CHU ◽  
CHI-CHANG CHEN

Service systems used for various applications in home automation and security require estimating the locations precisely using certain sensors. Serving a mobile user automatically by sensing his/her locations in an indoor environment is considered as a challenge. However, indoor localization cannot be carried out effectively using the Global Positioning System (GPS). In recent years, the use of Wireless Sensor Networks (WSNs) in locating a mobile object in an indoor environment has become popular. Some physical features have also been discussed to solve localization in WSNs. In this paper, we inquire into received signal strength indication (RSSI)-based solutions and propose a new localization scheme called the closer tracking algorithm (CTA) for indoor localization. Under the proposed CTA, a mechanism on mode-change is designed to switch automatically between the optimal approximately closer approach (ACA) and the real-time tracking (RTT) method according to pre-tuned thresholds. Furthermore, we design a mechanism to move reference nodes dynamically to reduce the uncovered area of the ACA for increasing the estimation accuracy. We evaluate the proposed CTA using ZigBee CC2431 modules. The experimental results show that the proposed CTA can determine the position accurately with an error distance less than 0.9 m. At the same time, the CTA scheme has at least 87% precision when the distance is less than 0.9 m. The proposed CTA can select an adaptive mode properly to improve the localization accuracy with high confidence. Moreover, the experimental results also show that the accuracy can be improved by the deployment and movement of reference nodes.


2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Chi Chen ◽  
Jyh-Ching Juang

The paper exploits the outlier detection techniques for wireless-sensor-network- (WSN-) based localization problem and proposes an outlier detection scheme to cope with noisy sensor data. The cheap and widely available measurement technique—received signal strength (RSS)—is usually taken into account in the indoor localization system, but the RSS measurements are known to be sensitive to the change of the environment. The paper develops an outlier detection scheme to deal with abnormal RSS data so as to obtain more reliable measurements for localization. The effectiveness of the proposed approach is verified experimentally in an indoor environment.


Fault Tolerant Reliable Protocol (FTRP) is proposed as a novel routing protocol designed for Wireless Sensor Networks (WSNs). FTRP offers fault tolerance reliability for packet exchange and support for dynamic network changes. The key concept used is the use of node logical clustering. The protocol delegates the routing ownership to the cluster heads where fault tolerance functionality is implemented. FTRP utilizes cluster head nodes along with cluster head groups to store packets in transient. In addition, FTRP utilizes broadcast, which reduces the message overhead as compared to classical flooding mechanisms. FTRP manipulates Time to Live values for the various routing messages to control message broadcast. FTRP utilizes jitter in messages transmission to reduce the effect of synchronized node states, which in turn reduces collisions. FTRP performance has been extensively through simulations against Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State (OLSR) routing protocols. Packet Delivery Ratio (PDR), Aggregate Throughput and End-to-End delay (E-2-E) had been used as performance metrics. In terms of PDR and aggregate throughput, it is found that FTRP is an excellent performer in all mobility scenarios whether the network is sparse or dense. In stationary scenarios, FTRP performed well in sparse network; however, in dense network FTRP’s performance had degraded yet in an acceptable range. This degradation is attributed to synchronized nodes states. Reliably delivering a message comes to a cost, as in terms of E-2-E. results show that FTRP is considered a good performer in all mobility scenarios where the network is sparse. In sparse stationary scenario, FTRP is considered good performer, however in dense stationary scenarios FTRP’s E-2-E is not acceptable. There are times when receiving a network message is more important than other costs such as energy or delay. That makes FTRP suitable for wide range of WSNs applications, such as military applications by monitoring soldiers’ biological data and supplies while in battlefield and battle damage assessment. FTRP can also be used in health applications in addition to wide range of geo-fencing, environmental monitoring, resource monitoring, production lines monitoring, agriculture and animals tracking. FTRP should be avoided in dense stationary deployments such as, but not limited to, scenarios where high application response is critical and life endangering such as biohazards detection or within intensive care units.


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