1,720,968 research outputs found
3D pedestrian dead reckoning and activity classification using waist-mounted inertial measurement unit
No full textIn this paper, an algorithm to estimate the position of a pedestrian in a 3-dimensional space is introduced. The proposed algorithm exploits the data provided by a waist-worn inertial platform and does not rely on the presence of any external infrastructure. Relevant features are extracted from the accelerometer data and are used to detect pedestrian activities such as standing, walking, going upstairs, or going downstairs. The estimate of the position is updated through a step detection procedure, which combines the signals provided by the inertial platform with the information about the pedestrian activity class
PDR and GPS trajectory parts matching for an improved self-contained personal navigation solution with handheld device
No full textThe evolution of smartphones and their embedded sensors motivates research toward the development of handheld device based navigation solutions especially for harsh environments. In this context, Pedestrian Dead Reckoning is usually adopted to compute the pedestrian's trajectory. Step/stride lengths and walking directions are combined in a recursive process. Unfortunately the estimated path suffers from drifting errors due to the sensors' nature and the motion complexity. To reduce this error, map matching strategies are studied and several solutions are proposed in the literature. In this work a Matching Filter is proposed to mitigate the drifting errors. The Matching Filter is a nest filter based on an Extended Kalman Filter and a Complementary filter. The key idea is to match the PDR trajectory with the standalone GPS trajectory during opportune phases in order to estimate a global heading and scale factor errors on the PDR path. The proposed strategy is tested with a 1km walk in a shopping center. A 75% improvement is found as compared to the PDR only trajectory
Hybrid map building for personal indoor navigation systems
No full textTracking the positions of people in large indoor spaces is important, since it enables a range of applications related to security, indoor navigation and guidance. This paper proposes a personal indoor navigation system based on hybrid map, containing geometric as well as symbolic information. In this way the same map can be exploited to guide and localise the user efficiently during navigation. The hybrid map is built using floor plans of the environment. It is a topological graph capturing the connectivity of complex indoor environment and it is retrieved by applying image-processing techniques. Some additional metric information are added to make the map suitable for quantitative localisation. Semantic features are considered to improve user readability
Augmenting rescuer safety using wireless sensor networks
No full textLocalization and tracking are fundamental features in emergency response operations, where the mission leader needs to be aware of the team location. This paper addresses the localization for rescuers by exploiting wireless sensor networks embedded in the environment. Specifically, a pre-deployed network is considered and a localization algorithm is designed to find the location of the node and to track the rescuers cooperatively. Nodes estimate their own positions, while rescuers improve and augment their location awareness during mission by navigating across via points suggested by the network, thus improving the overall localizability. Experimental results show the effectiveness of the approach
Improving the safety and the operational efficiency of emergency operators via on field situational awareness
No full textIn rescue missions, the situational awareness represents an essential tool in supporting rescue team operating in unknown and complex indoor environments. In case of fire in highly congested industrial scenarios (e.g., refineries, oil depots, petrochemical plants, etc.), the smoke may reduce the awareness of the rescuer about potential local resources/hazards, affecting both operational efficiency and personal safety. The mitigation of potential consequences arising from major accidents can be limited providing the emergency staff with tools able to foster their role on field. In this paper, we present the RISING (indooR localization and building maintenance using radio frequency Identification and inertial NaviGation) project that is devoted to support on field operators supplying them with a system for situational awareness and personal indoor positioning. The RISING solution is based on the integration of the RFID technology with the inertial navigation. A set of RFID tags, conveniently preinstalled in the working environment, can store information about their absolute position and the site of local items. This information can be easily retrieved on-the-fly using RFID readers and displayed on smart devices with which the user is equipped (e.g., tablet and/or smartphone) to allow on field situational awareness
Hybrid Indoor Positioning System for First Responders
Full text linkIn the last decade, many efforts have been devoted to indoor localization and positioning. In this paper, a hybrid indoor localization system has been developed within the European project REFIRE for emergency situations. The REFIRE solution estimates the user's pose according to a prediction-correction scheme. The user is equipped with a waist-mounted inertial measurement unit and a radio frequency identification (RFID) reader. In the correction phase, the estimation is updated by means of geo-referenced information fetched from passive RFID tags predeployed into the environment. Accurate position correction is obtained through a deep analysis of the RFID system radiation patterns. To this end, extensive experimental trials have been performed to assess the RFID system performance, both in static and dynamic operating conditions. Experimental validation in realistic environments shows the effectiveness of the proposed indoor localization system, even during long-last missions and/or using a limited number of tags
RISING: Radio Frequency Identification and Inertial Navigation for Indoor Localization in Emergency Management and Building Maintenance
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