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Navigation based on symbolic space models

Baras, Karolina; Moreira, Adriano; Meneses, Filipe
Fonte: IEEE Xplore Publicador: IEEE Xplore
Tipo: Conferência ou Objeto de Conferência
Publicado em 15/09/2010 Português
Relevância na Pesquisa
48.67087%
Existing navigation systems are very appropriate for car navigation, but lack support for convenient pedestrian navigation and cannot be used indoors due to GPS limitations. In addition, the creation and the maintenance of the required models are costly and time consuming, and are usually based on proprietary data structures. In this paper we describe a navigation system based on a human inspired symbolic space model. We argue that symbolic space models are much easier to create and to maintain, and that they can support routing applications based on self-locating through the recognition of nearby features. Our symbolic space model is supported by a federation of servers where the spatial descriptions are stored, and which provide interfaces for feeding and querying the model. Local models residing in different servers may be connected between them, thus contributing to the system scalability.; Fundação para a Ciência e a Tecnologia (FCT)

Localization system for pedestrians based on sensor and information fusion

Anacleto, Ricardo; Figueiredo, Lino; Almeida, Ana; Novais, Paulo
Fonte: Institute of Electrical and Electronics Engineers (IEEE) Publicador: Institute of Electrical and Electronics Engineers (IEEE)
Tipo: Conferência ou Objeto de Conferência
Publicado em //2014 Português
Relevância na Pesquisa
59.283643%
Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device’s GPS chip. This means that in indoor or in more dense environments these applications don’t work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.; This work is funded by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project PEst- OE/EEI/UI0752/2014. The work of Ricardo Anacleto is supported by a doctoral grant by FCT SFRH/BD/70248/2010.

Data Fusion Algorithms for Multiple Inertial Measurement Units

Bancroft, Jared B.; Lachapelle, Gérard
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 29/06/2011 Português
Relevância na Pesquisa
39.235376%
A single low cost inertial measurement unit (IMU) is often used in conjunction with GPS to increase the accuracy and improve the availability of the navigation solution for a pedestrian navigation system. This paper develops several fusion algorithms for using multiple IMUs to enhance performance. In particular, this research seeks to understand the benefits and detriments of each fusion method in the context of pedestrian navigation. Three fusion methods are proposed. First, all raw IMU measurements are mapped onto a common frame (i.e., a virtual frame) and processed in a typical combined GPS-IMU Kalman filter. Second, a large stacked filter is constructed of several IMUs. This filter construction allows for relative information between the IMUs to be used as updates. Third, a federated filter is used to process each IMU as a local filter. The output of each local filter is shared with a master filter, which in turn, shares information back with the local filters. The construction of each filter is discussed and improvements are made to the virtual IMU (VIMU) architecture, which is the most commonly used architecture in the literature. Since accuracy and availability are the most important characteristics of a pedestrian navigation system...

Height Compensation Using Ground Inclination Estimation in Inertial Sensor-Based Pedestrian Navigation

Park, Sang Kyeong; Suh, Young Soo
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 15/08/2011 Português
Relevância na Pesquisa
58.51757%
In an inertial sensor-based pedestrian navigation system, the position is estimated by double integrating external acceleration. A new algorithm is proposed to reduce z axis position (height) error. When a foot is on the ground, a foot angle is estimated using accelerometer output. Using a foot angle, the inclination angle of a road is estimated. Using this road inclination angle, height difference of one walking step is estimated and this estimation is used to reduce height error. Through walking experiments on roads with different inclination angles, the usefulness of the proposed algorithm is verified.

Indoor Pedestrian Navigation Using Foot-Mounted IMU and Portable Ultrasound Range Sensors

Girard, Gabriel; Côté, Stéphane; Zlatanova, Sisi; Barette, Yannick; St-Pierre, Johanne; van Oosterom, Peter
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 02/08/2011 Português
Relevância na Pesquisa
49.0758%
Many solutions have been proposed for indoor pedestrian navigation. Some rely on pre-installed sensor networks, which offer good accuracy but are limited to areas that have been prepared for that purpose, thus requiring an expensive and possibly time-consuming process. Such methods are therefore inappropriate for navigation in emergency situations since the power supply may be disturbed. Other types of solutions track the user without requiring a prepared environment. However, they may have low accuracy. Offline tracking has been proposed to increase accuracy, however this prevents users from knowing their position in real time. This paper describes a real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods. The system uses a combination of four techniques: foot-mounted IMU (Inertial Motion Unit), ultrasonic ranging, particle filtering and model-based navigation. The very purpose of the project is to combine these four well-known techniques in a novel way to provide better indoor tracking results for pedestrians.

Use of Earth’s Magnetic Field for Mitigating Gyroscope Errors Regardless of Magnetic Perturbation

Afzal, Muhammad Haris; Renaudin, Valérie; Lachapelle, Gérard
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 30/11/2011 Português
Relevância na Pesquisa
29.695203%
Most portable systems like smart-phones are equipped with low cost consumer grade sensors, making them useful as Pedestrian Navigation Systems (PNS). Measurements of these sensors are severely contaminated by errors caused due to instrumentation and environmental issues rendering the unaided navigation solution with these sensors of limited use. The overall navigation error budget associated with pedestrian navigation can be categorized into position/displacement errors and attitude/orientation errors. Most of the research is conducted for tackling and reducing the displacement errors, which either utilize Pedestrian Dead Reckoning (PDR) or special constraints like Zero velocity UPdaTes (ZUPT) and Zero Angular Rate Updates (ZARU). This article targets the orientation/attitude errors encountered in pedestrian navigation and develops a novel sensor fusion technique to utilize the Earth’s magnetic field, even perturbed, for attitude and rate gyroscope error estimation in pedestrian navigation environments where it is assumed that Global Navigation Satellite System (GNSS) navigation is denied. As the Earth’s magnetic field undergoes severe degradations in pedestrian navigation environments, a novel Quasi-Static magnetic Field (QSF) based attitude and angular rate error estimation technique is developed to effectively use magnetic measurements in highly perturbed environments. The QSF scheme is then used for generating the desired measurements for the proposed Extended Kalman Filter (EKF) based attitude estimator. Results indicate that the QSF measurements are capable of effectively estimating attitude and gyroscope errors...

Benefits of Combined GPS/GLONASS with Low-Cost MEMS IMUs for Vehicular Urban Navigation

Angrisano, Antonio; Petovello, Mark; Pugliano, Giovanni
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 19/04/2012 Português
Relevância na Pesquisa
38.649111%
The integration of Global Navigation Satellite Systems (GNSS) with Inertial Navigation Systems (INS) has been very actively researched for many years due to the complementary nature of the two systems. In particular, during the last few years the integration with micro-electromechanical system (MEMS) inertial measurement units (IMUs) has been investigated. In fact, recent advances in MEMS technology have made possible the development of a new generation of low cost inertial sensors characterized by small size and light weight, which represents an attractive option for mass-market applications such as vehicular and pedestrian navigation. However, whereas there has been much interest in the integration of GPS with a MEMS-based INS, few research studies have been conducted on expanding this application to the revitalized GLONASS system. This paper looks at the benefits of adding GLONASS to existing GPS/INS(MEMS) systems using loose and tight integration strategies. The relative benefits of various constraints are also assessed. Results show that when satellite visibility is poor (approximately 50% solution availability) the benefits of GLONASS are only seen with tight integration algorithms. For more benign environments, a loosely coupled GPS/GLONASS/INS system offers performance comparable to that of a tightly coupled GPS/INS system...

Design and Testing of a Multi-Sensor Pedestrian Location and Navigation Platform

Morrison, Aiden; Renaudin, Valérie; Bancroft, Jared B.; Lachapelle, Gérard
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 19/03/2012 Português
Relevância na Pesquisa
39.075803%
Navigation and location technologies are continually advancing, allowing ever higher accuracies and operation under ever more challenging conditions. The development of such technologies requires the rapid evaluation of a large number of sensors and related utilization strategies. The integration of Global Navigation Satellite Systems (GNSSs) such as the Global Positioning System (GPS) with accelerometers, gyros, barometers, magnetometers and other sensors is allowing for novel applications, but is hindered by the difficulties to test and compare integrated solutions using multiple sensor sets. In order to achieve compatibility and flexibility in terms of multiple sensors, an advanced adaptable platform is required. This paper describes the design and testing of the NavCube, a multi-sensor navigation, location and timing platform. The system provides a research tool for pedestrian navigation, location and body motion analysis in an unobtrusive form factor that enables in situ data collections with minimal gait and posture impact. Testing and examples of applications of the NavCube are provided.

Pedestrian Navigation Based on a Waist-Worn Inertial Sensor

Alvarez, Juan Carlos; Alvarez, Diego; López, Antonio; González, Rafael C.
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 03/08/2012 Português
Relevância na Pesquisa
48.72028%
We present a waist-worn personal navigation system based on inertial measurement units. The device makes use of the human bipedal pattern to reduce position errors. We describe improved algorithms, based on detailed description of the heel strike biomechanics and its translation to accelerations of the body waist to estimate the periods of zero velocity, the step length, and the heading estimation. The experimental results show that we are able to support pedestrian navigation with the high-resolution positioning required for most applications.

Use of High Sensitivity GNSS Receiver Doppler Measurements for Indoor Pedestrian Dead Reckoning

He, Zhe; Renaudin, Valérie; Petovello, Mark G.; Lachapelle, Gérard
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 28/03/2013 Português
Relevância na Pesquisa
38.96435%
Dead-reckoning (DR) algorithms, which use self-contained inertial sensors combined with gait analysis, have proven to be effective for pedestrian navigation purposes. In such DR systems, the primary error is often due to accumulated heading drifts. By tightly integrating global navigation satellite system (GNSS) Doppler measurements with DR, such accumulated heading errors can usually be accurately compensated. Under weak signal conditions, high sensitivity GNSS (HSGNSS) receivers with block processing techniques are often used, however, the Doppler quality of such receivers is relatively poor due to multipath, fading and signal attenuation. This often limits the benefits of integrating HSGNSS Doppler with DR. This paper investigates the benefits of using Doppler measurements from a novel direct vector HSGNSS receiver with pedestrian dead-reckoning (PDR) for indoor navigation. An indoor signal and multipath model is introduced which explains how conventional HSGNSS Doppler measurements are affected by indoor multipath. Velocity and Doppler estimated by using direct vector receivers are introduced and discussed. Real experimental data is processed and analyzed to assess the veracity of proposed method. It is shown when integrating HSGNSS Doppler with PDR algorithm...

Enhancing Indoor Inertial Pedestrian Navigation Using a Shoe-Worn Marker

Placer, Mitja; Kovačič, Stanislav
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 02/08/2013 Português
Relevância na Pesquisa
38.276855%
We propose a novel hybrid inertial sensors-based indoor pedestrian dead reckoning system, aided by computer vision-derived position measurements. In contrast to prior vision-based or vision-aided solutions, where environmental markers were used—either deployed in known positions or extracted directly from it—we use a shoe-fixed marker, which serves as positional reference to an opposite shoe-mounted camera during foot swing, making our system self-contained. Position measurements can be therefore more reliably fed to a complementary unscented Kalman filter, enhancing the accuracy of the estimated travelled path for 78%, compared to using solely zero velocities as pseudo-measurements.

Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng
Fonte: MDPI Publicador: MDPI
Tipo: Artigo de Revista Científica
Publicado em 07/05/2015 Português
Relevância na Pesquisa
28.842632%
Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV...

Exploration and analysis of sensor technologies for efficient indoor location-based services; Erfoschung und Analyse von Senortechnologien fuer die Implementierung effizienter Dienste zur Positionsbestimmung innerhalb Gebaeuden

Subramanian, Ponmalar Suguna
Fonte: Universidade de Tubinga Publicador: Universidade de Tubinga
Tipo: Dissertação
Português
Relevância na Pesquisa
28.84502%
In recent years, there is a mounting obligation for indoor location based services Comparable to outdoor location based services . Indoor guidance systems provide ample utilities to a user explicitly huge complex at shopping malls , hospitals and at vast libraries for any directed assistance. Pedestrian navigation is one such promising indoor location based service. Localization remains a basis for all location based services . Although, few pedestrian -based indoor localization are systems available in market , they lack either one of the attributes as such accuracy, reliability, scalability and / or expensive. GPS is not meant for indoors and even if so used at indoors , its relatively weak signal still stay a hurdle for any indoor location based services . In this dissertation , the aim is to build an efficient and precise indoor localization approach that can be implemented for most of the large indoor environments. The projected approach in this study incomparable to GPS that works outdoors will, remain eminently than other available indoor localization based approaches. All prerequisite for efficient localization such as accuracy, reliability, scalability, flexibility, availability, cost efficiency , minimum latency and robustness were evaluated reconstructed for this approach that is herewith demonstrated in my dissertation. The dissertation is structured as various chapters . Each of the chapter in this dissertation portrays novel methods utilizing major sensor technologies such as Bluetooth...

Person localization using sensor information fusion

Anacleto, Ricardo; Figueiredo, Lino; Almeida, Ana; Novais, Paulo
Fonte: Springer Publicador: Springer
Tipo: Conferência ou Objeto de Conferência
Publicado em //2014 Português
Relevância na Pesquisa
49.02227%
Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is di cult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to sup- press this limitation and to provide location everywhere (even where a structured environment doesn't exist) a wearable inertial navigation sys- tem is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.; This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT Fundao para a Cincia e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER- 028980 (PTDC/EEI-SII/1386/2012). Ricardo also acknowledge FCT for the support of his work through the PhD grant (SFRH/DB/70248/2010).

Localization system for pedestrians based on sensor and information fusion

Anacleto, Ricardo; Figueiredo, Lino; Almeida, Ana; Novais, Paulo
Fonte: IEEE Publicador: IEEE
Tipo: Conferência ou Objeto de Conferência
Publicado em //2014 Português
Relevância na Pesquisa
59.283643%
Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket

Deng, Zhi-An; Wang, Guofeng; Hu, Ying; Wu, Di
Fonte: MDPI Publicador: MDPI
Tipo: Artigo de Revista Científica
Publicado em 28/08/2015 Português
Relevância na Pesquisa
48.66385%
Heading estimation is a central problem for indoor pedestrian navigation using the pervasively available smartphone. For smartphones placed in a pocket, one of the most popular device positions, the essential challenges in heading estimation are the changing device coordinate system and the severe indoor magnetic perturbations. To address these challenges, we propose a novel heading estimation approach based on a rotation matrix and principal component analysis (PCA). Firstly, through a related rotation matrix, we project the acceleration signals into a reference coordinate system (RCS), where a more accurate estimation of the horizontal plane of the acceleration signal is obtained. Then, we utilize PCA over the horizontal plane of acceleration signals for local walking direction extraction. Finally, in order to translate the local walking direction into the global one, we develop a calibration process without requiring noisy compass readings. Besides, a turn detection algorithm is proposed to improve the heading estimation accuracy. Experimental results show that our approach outperforms the traditional uDirect and PCA-based approaches in terms of accuracy and feasibility.

Inertial Pocket Navigation System: Unaided 3D Positioning

Munoz Diaz, Estefania
Fonte: MDPI Publicador: MDPI
Tipo: Artigo de Revista Científica
Publicado em 17/04/2015 Português
Relevância na Pesquisa
48.86656%
Inertial navigation systems use dead-reckoning to estimate the pedestrian's position. There are two types of pedestrian dead-reckoning, the strapdown algorithm and the step-and-heading approach. Unlike the strapdown algorithm, which consists of the double integration of the three orthogonal accelerometer readings, the step-and-heading approach lacks the vertical displacement estimation. We propose the first step-and-heading approach based on unaided inertial data solving 3D positioning. We present a step detector for steps up and down and a novel vertical displacement estimator. Our navigation system uses the sensor introduced in the front pocket of the trousers, a likely location of a smartphone. The proposed algorithms are based on the opening angle of the leg or pitch angle. We analyzed our step detector and compared it with the state-of-the-art, as well as our already proposed step length estimator. Lastly, we assessed our vertical displacement estimator in a real-world scenario. We found that our algorithms outperform the literature step and heading algorithms and solve 3D positioning using unaided inertial data. Additionally, we found that with the pitch angle, five activities are distinguishable: standing, sitting, walking, walking up stairs and walking down stairs. This information complements the pedestrian location and is of interest for applications...

Step count algorithm adapted to indoor localization

Terra, Rui; Figueiredo, Lino; Barbosa, Ramiro S.; Anacleto, Ricardo
Fonte: ACM Press Publicador: ACM Press
Tipo: Conferência ou Objeto de Conferência
Publicado em //2013 Português
Relevância na Pesquisa
48.74047%
This paper presents a step count algorithm designed to work in real-time using low computational power. This proposal is our first step for the development of an indoor navigation system, based on Pedestrian Dead Reckoning (PDR). We present two approaches to solve this problem and compare them based in their error on step counting, as well as, the capability of their use in a real time system.

Design and Implementation of an Inertial Navigation System for Pedestrians Based on a Low-Cost MEMS IMU

Montorsi, Francesco; Pancaldi, Fabrizio; Vitetta, Giorgio M.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 07/03/2015 Português
Relevância na Pesquisa
48.86656%
Inertial navigation systems for pedestrians are infrastructure-less and can achieve sub-meter accuracy in the short/medium period. However, when low-cost inertial measurement units (IMU) are employed for their implementation, they suffer from a slowly growing drift between the true pedestrian position and the corresponding estimated position. In this paper we illustrate a novel solution to mitigate such a drift by: a) using only accelerometer and gyroscope measurements (no magnetometers required); b) including the sensor error model parameters in the state vector of an extended Kalman filter; c) adopting a novel soft heuristic for foot stance detection and for zero-velocity updates. Experimental results evidence that our inertial-only navigation system can achieve similar or better performance with respect to pedestrian dead-reckoning systems presented in related studies, although the adopted IMU is less accurate than more expensive counterparts.

AN INTELLIGENT PERSONAL NAVIGATOR INTEGRATING GNSS, RFID AND INS FOR CONTINUOUS POSITION DETERMINATION

RETSCHER, G.; UFPR; FU, Q.
Fonte: Universidade Federal do Paraná-UFPR Publicador: Universidade Federal do Paraná-UFPR
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; Artigo Avaliado pelos Pares Formato: application/pdf
Publicado em 11/03/2010 Português
Relevância na Pesquisa
39.11455%
Most of the developed pedestrian navigators rely on the use of satellite positioning (GNSS), sometimes also in combination with other sensors and positioning methods. In the project “Ubiquitous Cartography for Pedestrian Navigation” (UCPNAVI) we have integrated active Radio Frequency Identification (RFID) in combination with GNSS and Inertial Navigation Systems (INS) for continuous positioning. RFID can be employed in areas where no satellite positioning is possible due to obstructions, e.g. in urban canyons and indoor environments. In RFID positioning the location estimation  is based on Received Signal Strength Indication (RSSI) which is a measurement of the power present in a received radio signal. The receiver can compute its position using various methods based on RSSI. In total, three different methods have been developed and investigated, i.e., cell-based positioning, trilateration and RFID  location fingerprinting. These methods can be employed depending on the density of the RFID tags in the surrounding environment providing different levels of positioning accuracies. By integrating the three methods for positioning into an intelligent software package and developing a knowledge-based system it is possible  to determine the pedestrian position automatically and ubiquitously. The concept of the intelligent software package is presented and described in the paper. For improvement of the positioning accuracy of cell-based positioning a modification has been developed...