scholarly journals Cartographic Visualization for Indoor Semantic Wayfinding

2019 ◽  
Vol 3 (1) ◽  
pp. 22
Author(s):  
Nikolaos Bakogiannis ◽  
Charalampos Gkonos ◽  
Lorenz Hurni
Keyword(s):  
Indoor Navigation ◽  
Indoor Environments ◽  
Pedestrian Navigation ◽  
Navigation Assistance ◽  
The Third ◽  
Design Philosophy ◽  
Landmark Navigation ◽  
Cartographic Visualization ◽  
Human Participants ◽  
Benchmark Approach

In recent years, pedestrian navigation assistance has been used by an increasing number of people to support wayfinding tasks. Especially in unfamiliar and complex indoor environments such as universities and hospitals, the importance of an effective navigation assistance becomes apparent. This paper investigates the feasibility of the indoor landmark navigation model (ILNM) [1], a method for generating landmark-based routing instructions, by combining it with indoor route maps and conducting a wayfinding experiment with human participants. Within this context, three different cartographic visualization scenarios were designed and evaluated. Two of these scenarios were based on the implementation of the ILNM algorithm, with the concurrent effort to overcome the challenge of representing the semantic navigation instructions in two different ways. In the first scenario, the selected landmarks were visualized as pictograms, while in the second scenario, an axonometric-based design philosophy for the depiction of landmarks was followed. The third scenario was based on the benchmark approach (metric-based routing instructions) for conveying routing instructions to the users. The experiment showed that the implementation of the ILNM was feasible, and, more importantly, it was beneficial in terms of participants’ navigation performance during the wayfinding experiment, compared to the metric-based instructions scenario (benchmark for indoor navigation). Valuable results were also obtained, concerning the most suitable cartographic approach for visualizing the selected landmarks, while implementing this specific algorithm (ILNM). Finally, our findings confirm that the existence of landmarks, not only within the routing instructions, but also as cartographic representations on the route map itself, can significantly help users to position themselves correctly within an unfamiliar environment and to improve their navigation performance.

UWB and MEMS Based Indoor Navigation

2008 ◽  
Vol 61 (3) ◽  
pp. 369-384 ◽  
Author(s):  
Sylvain Pittet ◽  
Valérie Renaudin ◽  
Bertrand Merminod ◽  
Michel Kasser
Keyword(s):  
Indoor Navigation ◽  
Ultra Wideband ◽  
Indoor Environments ◽  
Selection Methods ◽  
Pedestrian Navigation ◽  
Radio Signals ◽  
Uwb Radio ◽  
Mechanical Sensors ◽  
Inertial Measurements ◽  
Reference Trajectories

Thanks to its physical characteristics, Ultra-wideband (UWB) is one of the most promising technologies for indoor pedestrian navigation. UWB radio localisation systems however experience multipath phenomena that decrease the precision and the reliability of the user's location. To cope with complex indoor environments, UWB radio signals are coupled with inertial measurements from Micro Electro Mechanical Sensors (MEMS) in an extended Kalman filter. Improved performances of the filter are presented and compared with reference trajectories and with pure inertial solutions. Only specific selection methods enable this improvement by detecting and removing outliers in the raw localisation data.

Constructing Floor Plan through Smoke Using Ultra Wideband Radar

2021 ◽  
Vol 5 (4) ◽  
pp. 1-29
Author(s):  
Weiyan Chen ◽  
Fusang Zhang ◽  
Tao Gu ◽  
Kexing Zhou ◽  
Zixuan Huo ◽  
...  
Keyword(s):  
Spatial Information ◽  
Low Cost ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Indoor Environments ◽  
Floor Plan ◽  
Construction Methods ◽  
Median Error ◽  
Indoor Scenarios

Floor plan construction has been one of the key techniques in many important applications such as indoor navigation, location-based services, and emergency rescue. Existing floor plan construction methods require expensive dedicated hardware (e.g., Lidar or depth camera), and may not work in low-visibility environments (e.g., smoke, fog or dust). In this paper, we develop a low-cost Ultra Wideband (UWB)-based system (named UWBMap) that is mounted on a mobile robot platform to construct floor plan through smoke. UWBMap leverages on low-cost and off-the-shelf UWB radar, and it is able to construct an indoor map with an accuracy comparable to Lidar (i.e., the state-of-the-art). The underpinning technique is to take advantage of the mobility of radar to form virtual antennas and gather spatial information of a target. UWBMap also eliminates both robot motion noise and environmental noise to enhance weak reflection from small objects for the robust construction process. In addition, we overcome the limited view of single radar by combining multi-view from multiple radars. Extensive experiments in different indoor environments show that UWBMap achieves a map construction with a median error of 11 cm and a 90-percentile error of 26 cm, and it operates effectively in indoor scenarios with glass wall and dense smoke.

scholarly journals Deep Learning-Based Positioning of Visually Impaired People in Indoor Environments

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6238
Author(s):  
Payal Mahida ◽  
Seyed Shahrestani ◽  
Hon Cheung
Keyword(s):  
Navigation System ◽  
Visually Impaired ◽  
Indoor Environment ◽  
Inertial Sensor ◽  
User Interaction ◽  
Indoor Navigation ◽  
Sensor Data ◽  
Indoor Environments ◽  
Visually Impaired People ◽  
Indoor Navigation System

Wayfinding and navigation can present substantial challenges to visually impaired (VI) people. Some of the significant aspects of these challenges arise from the difficulty of knowing the location of a moving person with enough accuracy. Positioning and localization in indoor environments require unique solutions. Furthermore, positioning is one of the critical aspects of any navigation system that can assist a VI person with their independent movement. The other essential features of a typical indoor navigation system include pathfinding, obstacle avoidance, and capabilities for user interaction. This work focuses on the positioning of a VI person with enough precision for their use in indoor navigation. We aim to achieve this by utilizing only the capabilities of a typical smartphone. More specifically, our proposed approach is based on the use of the accelerometer, gyroscope, and magnetometer of a smartphone. We consider the indoor environment to be divided into microcells, with the vertex of each microcell being assigned two-dimensional local coordinates. A regression-based analysis is used to train a multilayer perceptron neural network to map the inertial sensor measurements to the coordinates of the vertex of the microcell corresponding to the position of the smartphone. In order to test our proposed solution, we used IPIN2016, a publicly-available multivariate dataset that divides the indoor environment into cells tagged with the inertial sensor data of a smartphone, in order to generate the training and validating sets. Our experiments show that our proposed approach can achieve a remarkable prediction accuracy of more than 94%, with a 0.65 m positioning error.

Localization and Mapping for Indoor Navigation

2020 ◽  
pp. 930-954 ◽  
Author(s):  
Heba Gaber ◽  
Mohamed Marey ◽  
Safaa Amin ◽  
Mohamed F. Tolba
Keyword(s):  
System Architecture ◽  
Large Range ◽  
Simultaneous Localization And Mapping ◽  
Indoor Navigation ◽  
Indoor Environments ◽  
Challenging Problem ◽  
Unknown Environments ◽  
Localization And Mapping ◽  
Robotic Missions

Mapping and exploration for the purpose of navigation in unknown or partially unknown environments is a challenging problem, especially in indoor environments where GPS signals can't give the required accuracy. This chapter discusses the main aspects for designing a Simultaneous Localization and Mapping (SLAM) system architecture with the ability to function in situations where map information or current positions are initially unknown or partially unknown and where environment modifications are possible. Achieving this capability makes these systems significantly more autonomous and ideal for a large range of applications, especially indoor navigation for humans and for robotic missions. This chapter surveys the existing algorithms and technologies used for localization and mapping and highlights on using SLAM algorithms for indoor navigation. Also the proposed approach for the current research is presented.

Immune Buildings - Using Ergonomics and Environmental Design to Create Safe and Secure Settings

2002 ◽  
Vol 46 (9) ◽  
pp. 859-859
Author(s):  
Alan Hedge
Keyword(s):  
Human Factors ◽  
Terrorist Attack ◽  
Environmental Design ◽  
Airport Security ◽  
Indoor Environments ◽  
Sexual Assaults ◽  
The Third ◽  
Design Changes ◽  
Building Ventilation ◽  
Building Designs

The horrendous events in September of last year, from airplane attacks on large buildings to bioterrorism in postal and other government facilities, raised awareness of the vulnerability many modern buildings to terrorist attack and the importance of designing safer buildings that impede terrorist activity and that can facilitate occupant egress at a time of crisis. This symposium will examine the role that Human Factors professionals can play in improving the design of Immune Buildings, designed to better protect occupants and minimize the risks of hostile activity. Four papers will be presented that will examine human factors contributions to new ways of thinking about buildings. The first paper by James Wise will describe approaches to de-opportunizing such undesirable behaviors and environmental design changes that can thwart vandalism, burglaries, bank robberies, physical and sexual assaults, and counterterrorist situations. The second paper by Jake Pauls will review opportunities for changing building designs to impede terrorist ingress and facilitate occupant egress in times of need. The third paper by Alan Hedge will review ways that building ventilation systems can be configured to minimize bioterrorist threats on indoor environments by implementing a concept of ‘smart furniture’. The fourth paper by Eric Neiderman will examine the contributions that human factors can make to improving airport security.

scholarly journals Monocular Vision SLAM for Indoor Aerial Vehicles

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Koray Çelik ◽  
Arun K. Somani
Keyword(s):  
Indoor Navigation ◽  
Monocular Vision ◽  
Indoor Environments ◽  
Feature Points ◽  
Monocular Camera ◽  
Aerial Vehicles ◽  
Navigation Strategy ◽  
Aerial Vehicle ◽  
Technological Challenge ◽  
Limited Sensing

This paper presents a novel indoor navigation and ranging strategy via monocular camera. By exploiting the architectural orthogonality of the indoor environments, we introduce a new method to estimate range and vehicle states from a monocular camera for vision-based SLAM. The navigation strategy assumes an indoor or indoor-like manmade environment whose layout is previously unknown, GPS-denied, representable via energy based feature points, and straight architectural lines. We experimentally validate the proposed algorithms on a fully self-contained microaerial vehicle (MAV) with sophisticated on-board image processing and SLAM capabilities. Building and enabling such a small aerial vehicle to fly in tight corridors is a significant technological challenge, especially in the absence of GPS signals and with limited sensing options. Experimental results show that the system is only limited by the capabilities of the camera and environmental entropy.

scholarly journals AUTOMATICALLY DETERMINING SCALE WITHIN UNSTRUCTURED POINT CLOUDS

2016 ◽  
Vol XLI-B3 ◽  
pp. 617-624
Author(s):  
Jayren Kadamen ◽  
George Sithole
Keyword(s):  
Three Dimensional ◽  
Point Clouds ◽  
Indoor Navigation ◽  
Indoor Environments ◽  
Terrestrial Lidar ◽  
Detection Of Objects ◽  
The Difference ◽  
Computationally Intensive ◽  
Three Dimensional Models ◽  
General Size

Three dimensional models obtained from imagery have an arbitrary scale and therefore have to be scaled. Automatically scaling these models requires the detection of objects in these models which can be computationally intensive. Real-time object detection may pose problems for applications such as indoor navigation. This investigation poses the idea that relational cues, specifically height ratios, within indoor environments may offer an easier means to obtain scales for models created using imagery. The investigation aimed to show two things, (a) that the size of objects, especially the height off ground is consistent within an environment, and (b) that based on this consistency, objects can be identified and their general size used to scale a model. To test the idea a hypothesis is first tested on a terrestrial lidar scan of an indoor environment. Later as a proof of concept the same test is applied to a model created using imagery. The most notable finding was that the detection of objects can be more readily done by studying the ratio between the dimensions of objects that have their dimensions defined by human physiology. For example the dimensions of desks and chairs are related to the height of an average person. In the test, the difference between generalised and actual dimensions of objects were assessed. A maximum difference of 3.96% (2.93<i>cm</i>) was observed from automated scaling. By analysing the ratio between the heights (distance from the floor) of the tops of objects in a room, identification was also achieved.

scholarly journals OUTDOOR and INDOOR VISION BASED LOCALIZATION FOR BLIND PEDESTRIAN NAVIGATION ASSISTANCE

2020 ◽  
Vol 04 (12) ◽  
pp. 715-720
Author(s):  
K.Tasleem Banu ◽  
K Supriya ◽  
K Sony ◽  
M Chandana ◽  
M Bhavana ◽  
...  
Keyword(s):  
Pedestrian Navigation ◽  
Navigation Assistance ◽  
Vision Based Localization

scholarly journals INDOOR NAVIGATION ASSISTANCE SYSTEM USING BLUETOOTH

2016 ◽  
pp. 44-45
Author(s):  
APURVA MEHTA ◽  
D. D. PUKALE ◽  
RADHIKA BHAGAT ◽  
RUJAL SHAH
Keyword(s):  
Short Range ◽  
Low Cost ◽  
Indoor Navigation ◽  
Assistance System ◽  
Navigation Systems ◽  
Positioning Systems ◽  
Navigation Assistance ◽  
The Past ◽  
Current Location ◽  
Global Positioning

In the past few years, a number of ideas have been proposed for indoor navigation systems. These ideas were not as widely implemented as outdoor positioning systems like GPS(Global Positioning Systems). We propose an indoor navigation assistance system using Bluetooth which is low cost and feasible to use in daily life. Our system enables users with handheld mobile devices to steer with ease through the indoor premises using the short range radio frequencies of Bluetooth. It also establishes user’s current location and the various paths leading to the destination. Dijkstra’s algorithm is used to determine the shortest path from the source to the required destination.

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