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Location-based services (LBS) have an increasing demand for high accuracy but accurate positioning is available only for outdoor areas. Multiple indoor positioning algorithms have been researched and improved to provide better accuracy. For the purpose of the internet of things Bluetooth 4 (BLE) was introduced. However, a Bluetooth 4 signal is highly affected by obstruction attenuation and multipath...
A routing graph allows to find paths in buildings quickly. Raster images of floor plans are simple to obtain but display poor performance. A manually constructed graph is quite optimal if designed by an informed person, but the process is time consuming and expensive. We describe a fast method to calculate a 2D routing graph from raster images. We adapt image processing techniques and apply a conditional...
Recently, a compact receiver structure, containing a set of apertures and photo diodes (PDs) that are arranged to offer good angular diversity, was proposed for visible light communication [1]. In [2], this receiver structure was considered for visual light positioning (VLP), where the positioning accuracy for direct estimation of the position was evaluated using the Cramer-Rao Lower bound. However,...
In recent research, indoor localisation systems are often based upon a recursive state estimation using particle filtering. Within this context, sample impoverishment is a crucial problem causing the position estimation to lose track or get stuck within a demarcated area. The sample impoverishment problem can therefore be described as a too small particle diversity, unable to sample enough particles...
Some location-aware use cases imply that a person desires to find an object relative to his position. This is the case of museum visits or any indoors/outdoors activity where the objects of interest are not geo-referenced or even can move with time. For these use cases, a user does not need an absolute localization, but a relative information consisting of the range to the object and the heading angle...
In this paper, a strides detection algorithm is proposed using inertial sensors worn on the ankle. This innovative approach based on geometric patterns can detect both normal walking strides and atypical strides such as small steps, side steps and backward walking that existing methods struggle to detect. It is also robust in critical situations, when for example the wearer is sitting and moving the...
We present an automatic spatial-segmentation method for a novel magnetic-field hybrid indoor positioning system. Unlike conventional approaches that implement magnetic field alone for the whole experimental space, our approach employs an efficient automatic segmentation method to make up the constraints of magnetic-field indoor positioning after fully evaluating local magnetic-field characteristics...
This paper studies heading estimation jointly with the attitude and position estimation of a rigid body equipped with inertial and magnetic sensors in indoor environment. In contrast with other indoor dead-reckoning approaches, no assumption is made about the nature of the movement or environment layout. Based on a previous paper, an Extended Kalman Filter is designed, which includes inertial sensor...
The industrial demands for accurate localization systems have been rapidly increasing after the introduction of the Internet of Things (IoT) concept. Self localization and tracking transmitting sources are considered essential parts of IoT applications. In this paper we studied the possibility of applying angle of arrival (AoA) estimations to localize an IoT transceiver device in an indoor environment...
This work presents a study to determine the improvement of the simultaneous position estimations of several Mobile Robots (MRs) adding the relative distances between them, regarding independent position estimations for each MR. To evaluate the performance of the proposal, it is supposed that the localization scenario is composed of an Ultrasonic Local Positioning System (ULPS) and two MRs with odometry...
This paper considers the problem of decentralized, cooperative, and dynamic self-localization in wireless sensor networks. In particular, we are interested in a restrictive but very realistic scenario where few anchors are deployed and each anchor whose location is priori known may only communicate with very few agents (e.g. just one agent) whose location is unknown and to-be-estimated. The lack of...
This paper considers the problem of range-based decentralized localization in wireless sensor networks when the impulsive measurement noise is present. We develop a robust localization estimator requiring no a priori knowledge of the noise distribution. The approach to robust localization presented here follows the concept of M-estimation and is implemented in a decentralized manner thus suiting the...
In this paper, an indoor vehicle multi-level positioning algorithm is proposed that makes use of an indoor map, as well as dead-reckoning sensor information that is available in every car. A particle filter framework is used for online optimal Bayesian vehicle positioning with indoor-outdoor transitions. The method is validated experimentally in two indoor multi-level car parks. The achieved results...
Magnetic fields are used for localization and navigation in the field of robotics. In recent years, because of the spread of mobile devices equipped with magnetic sensors (e.g., smart phones), the use of magnetic fields has been extensive, especially for position tracking of mobile devices. One example application of such tracking is in identifying the position of a person with a mobile device. Development...
This objective of this paper is to propose and evaluate a new algorithm to increase the computation and storage efficiency and to reduce the bandwidth requirements of the Wi-Fi received signal strength indicator (RSSI) maps based on Gaussian Process (GP) models. GP models are non-parametric models that estimate the likelihood function of the target variable, in this case the Wi-Fi RSSI values, conditioned...
Positioning services are increasingly used for applications such as navigation, advertising and social media. While outdoor navigation based on GPS and/or cellular systems works well, indoor navigation is a much tougher challenge. This paper proposes an indoor localization using Wi-Fi received signal strength indicator (RSSI) measurements from existing access points. Using RSSI data from multiple...
We present a maximum likelihood estimator for estimating the positions of accelerometers in an inertial sensor array. This method simultaneously estimates the positions of the accelerometers and the motion dynamics of the inertial sensor array and, therefore, does not require a predefined motion sequence nor any external equipment. Using an iterative block coordinate descent optimization strategy,...
Numerous attempts have been made to estimate position using Wi-Fi signals. Radio map, which is the collection of the received signal strength indicator (RSSI) of Wi-Fi signals along with their collected location information, is essential for the estimation of positon in a high resolution. However, the radio map construction is not only labor intensive, but also it requires periodic updates to cope...
Map retrieval, the problem of similarity search over a large collection of 2D pointset maps previously built by mobile robots, is crucial for autonomous navigation in indoor and outdoor environments. Bag-of-words (BoW) methods constitute a popular approach to map retrieval; however, these methods have extremely limited descriptive ability because they ignore the spatial layout information of the local...
Wearable devices have many applications, pedestrian navigation among them. In this case, the inertial measurement unit (IMU) is embedded in the wearable device. Moreover, inertial navigation systems (INSs) based on non-foot-mounted IMUs use the step-length-and-heading estimation approach. The latter requires the calibration of the empirical model to estimate the step length. In this work, we propose...
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