Low-cost Localization System Research Articles

RSSI Fingerprint Height Based Empirical Model Prediction for Smart Indoor Localization.

Smart indoor living advances in the recent decade, such as home indoor localization and positioning, has seen a significant need for low-cost localization systems based on freely available resources such as Received Signal Strength Indicator by the dense deployment of Wireless Local Area Networks (WLAN). The off-the-shelf user equipment (UE's) available at an affordable price across the globe are well equipped with the functionality to scan the radio access network for hearable single strength; in complex indoor environments, multiple signals can be received at a particular reference point with no consideration of the height of the transmitter and possible broadcasting coverage. Most effective fingerprinting algorithm solutions require specialized labor, are time-consuming to carry out site surveys, training of the data, big data analysis, and in most cases, additional hardware requirements relatively increase energy consumption and cost, not forgetting that in case of changes in the indoor environment will highly affect the fingerprint due to interferences. This paper experimentally evaluates and proposes a novel technique for Received Signal Indicator (RSSI) distance prediction, leveraging transceiver height, and Fresnel ranging in a complex indoor environment to better suit the path loss of RSSI at a particular Reference Point (RP) and time, which further contributes greatly to indoor localization. The experimentation in different complex indoor environments of the corridor and office lab during work hours to ascertain real-life and time feasibility shows that the technique's accuracy is greatly improved in the office room and the corridor, achieving lower average prediction errors at low-cost than the comparison prediction algorithms. Compared with the conventional prediction techniques, for example, with Access Point 1 (AP1), the proposed Height Dependence Path-Loss (HEM) model at 0 dBm error attains a confidence probability of 10.98%, higher than the 2.65% for the distance dependence of Path-Loss New Empirical Model (NEM), 4.2% for the Multi-Wall dependence on Path-Loss (MWM) model, and 0% for the Conventional one-slope Path-Loss (OSM) model, respectively. Online localization, amongst the hearable APs, it is seen the proposed HEM fingerprint localization based on the proposed HEM prediction model attains a confidence probability of 31% at 3 m, 55% at 6 m, 78% at 9 m, outperforming the NEM with 26%, 43%, 62%, 62%, the MWM with 23%, 43%, 66%, respectively. The robustness of the HEM fingerprint using diverse predicted test samples by the NEM and MWM models indicates better localization of 13% than comparison fingerprints.

Modeling of Leopard optimization based Node Localization Technique for Wireless Communication Networks

Wireless communication inculcates transfer of information not having any physical connection among two or more points. The significant operation of a sensor network becomes collecting and forwarding data to destiny. It is highly crucial to have an awareness regarding the place of collected data. This data is acquired by leveraging localization method in wireless sensor networks (WSNs). Localization is a way of determining the sensor nodes (SNs) location. Localization of SNs turns out to be an exciting research area, and several studies were performed till now. It is very favourable to model scalable, effectual, and low-cost localization systems for WSNs. This study develops a Leopard optimization based Node Localization Technique for Wireless Communication (LONLT-WC). The goal of the LONLT-WC model is to recognize the location of the nodes involved in the network. The LONLT-WC model involves the design of snow leopard optimization (SLO) algorithm, inspired from the characteristics of snow leopards. The presented LONLT-WC approach computes the unidentified location of the nodes utilizing anchor nodes in the network with the accomplishment of least error rate. The experimental analysis of the LONLT-WC model involves a series of simulations and the results highlighted the betterment of the presented technique.

Smart antenna with circular polarization for high accuracy indoor localization system

This article presents a new switched beam antenna (SBA) for indoor localization applications. The SBA consists of seven circularly polarized (CP) element antennas using a novel feeding network. The attractive characteristics of the proposed CP antenna are high gain, wide bandwidth (BW) with the BW of 36.2% at the reflection coefficient less than −10 dB (4.6–6.7 GHz), the 3 dB axial ratio (AR) BW of 22.4% (5.4–6.7 GHz), wide 3 dB AR beamwidth as about 60 degrees, and maximum gain of 9 dBi within the total bandwidth. Experimental results show good agreement with simulated ones in terms of radiation pattern, AR, and reflection coefficient. We proposed a low-cost and simple RF-based indoor localization system based on a single anchor node equipped with this SBA. The system is demonstrated through experimental validations in a 6 m × 6.5 m × 3.5 m office room with a mean localization error of 0.72 m.

Towards a low-cost localization system for small ruminants

Monitoring the activity and location of weeding flocks bears distinctive benefits to the livestock industry. Among other benefits, access to this kind of data allows farmers to manage pastures more effectively, monitor the animal’s reproductive cycles and health condition, as well as detect threats from external agents, such as attacks from predators or thieves.The scarcity of human shepherds, together with the significant and increasing costs associated with such activity, fostered the research of ICT technologies as a means to automate the collection of location data. GPS trackers are the most popular solution, but they are expensive and have high power consumption, thus impairing its use for small ruminant flocks. Consequently, alternative solutions, such as the ones based on advanced Range-RSSI-based algorithms are potentially more attractive, especially when a communication infrastructure already exists. This is the strategy followed in the scope of the SheepIT project, whose localization mechanism is presented in detail in this paper. Together with the localization mechanism, the farm radio infrastructure allows tracking animals in real-time. To evaluate the localization system performance, this paper compares the results of the implemented framework with the results obtained when using a commercial GPS tracker. Although GPS allows obtaining a better accuracy, the RSSI-based mechanism herein proposed allows, in certain conditions, attaining accuracy levels that meet the requirements of this type of application, without requiring additional hardware and with residual power consumption.

Special Issue: Localization in Wireless Sensor Networks

Recent and continuous development of mobile computing and user-centric applications has led to a requirement for accurate and low-cost localization and tracking systems [...]

A High-Efficient and Low-Cost Localization System for Wireless Sensor Networks

The problem of localization of wireless sensor nodes has long been regarded as very difficult to solve, when considering the realities of real world environments. In this paper, we formally describe, design, implement and evaluate a novel localization system, called Spotlight. Our system uses the spatio-temporal properties of well controlled events in the network (e.g., light), to obtain the locations of sensor nodes. We demonstrate that a high accuracy in localization can be achieved without the aid of expensive hardware on the sensor nodes, as required by other localization systems. We evaluate the performance of our system in deployments of Mica2 and XSM motes. Through performance evaluations of a real system deployed outdoors, we obtain a 20cm localization error. A sensor network, with any number of nodes, deployed in a 2500m2 area, can be localized in under 10 minutes, using a device that costs less than $1000. To the best of our knowledge, this is the first report of a sub-meter localization error, obtained in an outdoor environment, without equipping the wireless sensor nodes with specialized ranging hardware.

A Survey of the State-of-the-Art Localization Techniques and Their Potentials for Autonomous Vehicle Applications

For an autonomous vehicle to operate safely and effectively, an accurate and robust localization system is essential. While there are a variety of vehicle localization techniques in literature, there is a lack of effort in comparing these techniques and identifying their potentials and limitations for autonomous vehicle applications. Hence, this paper evaluates the state-of-the-art vehicle localization techniques and investigates their applicability on autonomous vehicles. The analysis starts with discussing the techniques which merely use the information obtained from on-board vehicle sensors. It is shown that although some techniques can achieve the accuracy required for autonomous driving but suffer from the high cost of the sensors and also sensor performance limitations in different driving scenarios (e.g., cornering and intersections) and different environmental conditions (e.g., darkness and snow). This paper continues the analysis with considering the techniques which benefit from off-board information obtained from V2X communication channels, in addition to vehicle sensory information. The analysis shows that augmenting off-board information to sensory information has potential to design low-cost localization systems with high accuracy and robustness, however, their performance depends on penetration rate of nearby connected vehicles or infrastructure and the quality of network service.

저가형 센서융합기반 정밀측위를 위한 코너검출 기반 도로표지판 검출

저가형 센서융합기반 정밀측위를 위한 코너검출 기반 도로표지판 검출

LOCALIZATION AND MOTION CONTROL IMPLEMENTATION FOR AN AGRICULTURAL MOBILE ROBOT

In robot navigation experiment, a localization and motion control system is required to secure the agricultural robot motion in the environment. However, the high cost of localization system and complex structure of motion controller has limited the low cost agricultural mobile robot development. In this paper, a low-cost localization system and simple motion control system is presented. The localization system has been implemented using a dead reckoning method by accessing an incremental encoder’s reading. A simple cascaded motion control system based on proportional feedback kinematics controller and PI based controller was used to control the mobile robot motion. The performances of different turning methods: U turn and a π turn, were compared for lane changing, based on completion time, controller’s error and distance travelled. Simulation test of robot motion was conducted using a Simulink3d animation in MATLAB software. An experimental test in a real greenhouse environment was conducted to verify the simulation performance in motion control and localization system. The experimental and simulation results have shown that a U turn has the best turning performance with 69.1 % better efficiency in experimental mode and it is recommended to be applied in agricultural field.

Indoor low-cost localization system for controlling aerial robots

This paper presents a low-cost localization system to guide an Unmanned Aerial Vehicle (UAV) in indoor flights, considering an environment with invariant texture and typical indoor illumination. The first contribution of the paper is the proposal of a system to estimate the position and orientation of the UAV, through a multi-sensor fusion scheme, dealing with data provided by a RGB-D sensor, an inertial measurement unit (IMU), an ultrasonic sensor and optical flow-based velocity estimates. A second contribution of the paper is the proposal of a high-level control system to guide the UAV in path-following tasks, involving two controllers: a kinematic one, responsible for generating reference velocities for the vehicle, and a PD one, responsible for tracking such reference velocities, thus characterizing a cascade controller. Experiments with such a localization and control systems, during which abrupt disturbances are applied, were carried out to check the effectiveness of the developed capture and control systems, whose results validate the proposed framework.

A Low-Cost RSSI-Based Localization System for Wildlife Tracking

This paper presents a low-cost localization system for the high-resolution tracking of bats. The system bases on a ground network consisting of multiple low-cost receiver stations, and ultra-lightweight transmitters mounted on the bats. A main challenge of the received signal strength based localization is the limited dynamic range of the employed low-cost receivers. This challenge is solved using an efficient 2-stage differential correlation concept. It significantly improves the dynamic wrt. conventional power detection methods. In addition, this concept requires low processing power and is robust wrt. frequency offsets. Finally, this paper presents a performance evaluation employing reference measurements recorded in the rain forest of Panama.

Lane Marking-Based Vehicle Localization Using Low-Cost GPS and Open Source Map

Autonomous Vehicle applications and Advanced Driving Assistance Systems (ADAS) need scene understanding processes, allowing high-level systems to carry out decision. For such systems, the localization of a vehicle evolving in a structured dynamic environment constitutes a complex problem of crucial importance. However, the low accuracy of the global positioning system (GPS) system in urban environments makes its localization unreliable for further treatments. The combination of GPS data and additional sensors (WSS, IMU or Camera) can improve the localization precision. More and more, digital maps are also used in this process. Generally, these maps are customized or built for a specific application, asking high-cost to design and upgrade. In this paper, we propose a low-cost localization system based on camera, GPS and open map. Starting from the road marking, detected by a multi-kernel estimation method, a particle filter generates the samples taking advantage of lane markings to predict the most probable trajectory of the vehicle and the low-cost GPS position. Then, the accuracy of the localization is improved using an open map. This process was validated through several scenarios with a public database and our experimental platform.

A Distributed UWB-based Localization System in Underground Mines

The location of people, mobile terminals and equipment is highly desirable for operational enhancements in the mining industry. In an indoor environment such as a mine, the multipath caused by reflection, diffraction and diffusion on the rough sidewall surfaces are the main sources of range measurement errors. In this paper, a UWB time of flight based localization system is proposed to address the multipath effect in underground mines. To reduce the communication cost and time delay of localization in such a chain type wireless network, a distributed localization algorithm based on particle swarm optimization (PSO) is proposed and implemented on the blind node (the node to be localized). Without extra hardware needed, an accurate but low cost localization system has been achieved. Experimental results verify the proposed scheme

An Application of a Low-Cost Monitoring and Guidance System in a WSN

Wireless sensor networks (WSNs) have been deployed in many workplaces (hangars, warehouses, etc.) for general purposes (climatic data collection, security and so on). Also, in these kinds of workplaces, localization systems are often required for monitoring, tracking and guidance, but this means extra charge. In this article, an application of a low-cost localization system, which can track and guide vehicles by the help of an existing WSN system, is introduced. For the system, a technique called “Edge-Masking Technique” was proposed. Besides, “Bounding Box” method was used for the position detection. The empiric RSSI-distance relationship equation used in the method was obtained from experimental studies. In addition to this, the equation was improved by a technique named “Circular Calibration with Offset Value”. The practicability of the system was demonstrated by both simulation and real nodes.

Evaluating different landmark positioning systems within the RIDE architecture

Mobile robots operating in the real world need a very reliable localization system to navigate autonomously for long periods of time. Numerous methods for indoor mobile robot localization have been developed. However, an affordable system covering all environments and situations is not yet available. Therefore, it is very important for mobile robot application developers to be aware of the operation and limitations of the different localization systems in order to obtain the best performance for each case. This paper evaluates two indoor localization systems that are integrated in the RIDE architecture: a commercial (Hagisonic StarGazer) and a low cost localization system based on the popular Wii remote control (WiiMote) with different tag distributions were evaluated. Characteristics that were tested include precision, accuracy, reliability, cost and immunity to interference.

On the Joint Estimation of the RSS-Based Location and Path-loss Exponent

Due to its straightforward implementation, the received signal strength (RSS) has been an advantageous approach for low cost localization systems. Although the propagation model is difficult to characterize in uncertain environments, the majority of current studies assume to have exact knowledge of the path-loss exponent (PLE). This letter deals with RSS based localization in an unknown path-loss model. First, we derive an analytical expression for the mean square error on location estimates for incorrect PLE assumption and examine, via simulation, the effects of error in the PLE on the location accuracy. Second, we enhance a previously proposed RSS-PLE joint estimator (JE) by reducing its complexity. We also propose a maximum a posteriori (MAP) estimator by considering the PLE as an unknown random variable. Finally, we derive the Hybrid Cramer Rao Bound (HCRB) as a benchmark for the MAP estimator. Error analysis results predict large error due to incorrect PLE assumption which are in agreement with the simulation results. Further simulations show that the MAP estimator exhibits better performance at low signal to noise ratio (SNR) and that the relation between the HCRB and CRB depends on the network geometry.

Low-Cost Laser-Based Localization System for Agricultural Machines

This paper describes the design and test of a low-cost localization system for agricultural applications, which determines a tractor position in fields up to 0.5 km with an uncertainty of about 1 m. The proposed system employs a standard unmodified laser head, which is commonly used for field leveling, plus a reference ground-fixed laser receiver and requires neither laser modulation nor expensive time-of-flight measurements of light beams