Outdoor Navigation Research Articles

Finding outdoor boundaries for 3D space‐based navigation

AbstractOutdoor navigation is widely used in daily life, but faces various issues related to the fidelity of outdoor navigation networks. For instance, agents (pedestrians) are often guided via unrealistic detours around places without clear paths (e.g., squares) or if there are vertical constraints such as overpasses/bridges. This is partly explained by the fact that the main sources of navigation networks in current outdoor navigation are two‐dimensional road/street networks. Utilizing a three‐dimensional space‐based navigation model, compatible with some indoor approaches, is a popular way to address the above‐mentioned issues. A 3D space‐based navigation model is generated by treating 3D spaces as nodes and the shared faces as edges. Inputs of this model are enclosed 3D spaces (volumes). However, outdoor spaces are generally open and unbounded. This article puts forward an approach to enclose outdoor spaces and mimic the indoor environments to derive a network based on connectivity and accessibility of spaces. The approach uses 2.5D maps and consists of three major steps: object footprint determination, footprint classification and space creation. Two use cases demonstrate the proposed approach. Enclosing outdoor spaces opens a new research direction toward providing seamless indoor/outdoor navigation for a range of agents.

Indoor Navigation Systems for Visually Impaired Persons: Mapping the Features of Existing Technologies to User Needs.

Currently, several outdoor navigation and orientation electronic traveling aid (ETA) solutions for visually impaired (VI) people are commercially available or in active development. This paper’s survey of blind experts has shown that after outdoor navigation, the second most important ETA feature for VI persons is indoor navigation and orientation (in public institutions, supermarkets, office buildings, homes, etc.). VI persons need ETA for orientation and navigation in unfamiliar indoor environments with embedded features for the detection and recognition of obstacles (not only on the ground but also at head level) and desired destinations such as rooms, staircases, and elevators. The development of such indoor navigation systems, which do not have Global Positioning System (GPS) locational references, is challenging and requires an overview and evaluation of existing systems with different navigation technologies. This paper presents an evaluation and comparison of state-of-the-art indoor navigation solutions, and the research implications provide a summary of the critical observations, some insights, and directions for further developments. The paper maps VI needs in relation to research and development (R&D) trends using the evaluation criteria deemed most important by blind experts.

A Low Cost Civil Vehicular Seamless Navigation Technology Based on Enhanced RISS/GPS between the Outdoors and an Underground Garage

Vehicles have to rely on satellite navigation in an open environment. However, satellite navigation cannot obtain accurate positioning information for vehicles in the interior of underground parking lots, as they comprise a semi-enclosed navigation space. Therefore, vehicular navigation needs to take into consideration both outdoor and indoor environments. Actually, outdoor navigation and indoor navigation require different positioning methods, and it is of great importance to choose a reasonable navigation and positioning algorithm solution for vehicles. Fortunately, the integrated navigation of the Global Positioning System (GPS) and the Micro-Electro-Mechanical System (MEMS) inertial navigation system could solve the problem of switching navigation algorithms in the entrance and exit of underground parking lots. This paper proposes a low cost vehicular seamless navigation technology based on the reduced inertial sensor system (RISS)/GPS between the outdoors and an underground garage. Specifically, the enhanced RISS is a positioning algorithm based on three inertial sensors and one odometer, which could achieve a similar location effect as the full model integrated navigation, reduce the costs greatly, and improve the efficiency of each sensor.

FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing

In this overview paper, data-driven learning model-based cooperative localization and location data processing are considered, in line with the emerging machine learning and big data methods. We first review (1) state-of-the-art algorithms in the context of federated learning, (2) two widely used learning models, namely the deep neural network model and the Gaussian process model, and (3) various distributed model hyper-parameter optimization schemes. Then, we demonstrate various practical use cases that are summarized from a mixture of standard, newly published, and unpublished works, which cover a broad range of location services, including collaborative static localization/fingerprinting, indoor target tracking, outdoor navigation using low-sampling GPS, and spatio-temporal wireless traffic data modeling and prediction. Experimental results show that near centralized data fitting- and prediction performance can be achieved by a set of collaborative mobile users running distributed algorithms. All the surveyed use cases fall under our newly proposed Federated Localization (FedLoc) framework, which targets on collaboratively building accurate location services without sacrificing user privacy, in particular, sensitive information related to their geographical trajectories. Future research directions are also discussed at the end of this paper.

Guiding and Navigation for the Blind using Deep Convolutional Neural Network Based Predictive Object Tracking

Indoor and outdoor Navigation is a tough task for a visually impaired person and they would most of the time require human assistance. Existing solutions to this problem are in the form of smart canes and wearable. Both of which use sensors like on - board proximity and obstacle detection, as well as a haptic or auditory feedback system to warn the user of stationary or incoming obstacles so that they do not collide with any of them as they move. This approach has many drawbacks as it is not yet a stand - alone reliable device for the user to trust when navigating, and when frequently triggered in crowded areas, the feedback system will confuse the user with too many requests resulting in loss of actual information. Our Goal here is to create a Personalized assistant to the user, which they can interact naturally with their voice to mimic the aid of an actual human assistance while they are on the move. It works by using its object detection module with a high reliability training accuracy to detect the boundaries of objects in motion per frame and once the bounding box crosses the threshold accuracy, recognize the object in the box and pass the information to the system core, where it verifies if the information needed to be passed onto the user or not, if yes it passes the converted speech information to the voice interaction model. The voice interaction model is consent-based, it would accept and respond to navigation queries from the user and will intelligently inform them about the obstacle which needs to be avoided. This ensures only the essential information in the form of voice requests is passed onto the user, which they can use to navigate and also interact with the assistant for more information.

Aerial and Under-water Dronal Communication: Potentials, Issues and Vulnerabilities

The use of UAVs has been on the rise since the past decade. These UAVs are very versatile and can be applied to several fields ranging from agriculture to military reconnaissance. Due to the immense functionality of the UAVs, it has now become a very popular topic in Research. With the advent of Deep Learning and Machine Learning the autonomous navigation functionalities have been improved but it still poses a challenge as navigating a drone involves the integration of its software and hardware functionalities. This paper reviews both indoor and outdoor navigation. Topics in navigation such as Control, Hardware, Algorithms, Path-Planning, and communication are touched upon in this paper. The paper also presents a discussion on the Navigation of UAVs using vision-based technologies, this technology encompasses the use of various sensors and cameras and integrate it with the navigation system of the UAV to ensure the success of UAV’s operation. UAVs play a pivotal role in networking, many applications have been developed which have UAVs as an important component in them. Their applications include Urban computing, Internet of Things, Ubiquitous Computing to name a few. Safely operating a UAV as a network node is not a simple task, these nodes are prone to various types of attacks. A new type of attack introduced in this paper is termed as “Coagulation Attack”. This attack gets its name from the coagulation property of fluids wherein fluids clot and their particles settle down. This paper explores the concept, issues, challenges and research aspects of Coagulation attack. This paper also introduces the concept of Underwater Wireless Communication. On a planet where 70% of the surface is covered in water, UWC has a lot of potentials to be exploited. Moreover UWC is critical in many key areas of Maritime research, commerce, and surveillance. UWC is used for experimental observation, data collection and analysis, underwater navigation, disaster prevention and early detection warning of a tsunami. In addition, we summarize emerging technologies in the UWC, future research directions and recommendations using fifth-generation (5G) communication techniques.

Magnetic-Map-Matching-Aided Pedestrian Navigation Using Outlier Mitigation Based on Multiple Sensors and Roughness Weighting.

This research proposes an algorithm that improves the position accuracy of indoor pedestrian dead reckoning, by compensating the position error with a magnetic field map-matching technique, using multiple magnetic sensors and an outlier mitigation technique based on roughness weighting factors. Since pedestrian dead reckoning using a zero velocity update (ZUPT) does not use position measurements but zero velocity measurements in a stance phase, the position error cannot be compensated, which results in the divergence of the position error. Therefore, more accurate pedestrian dead reckoning is achievable when the position measurements are used for position error compensation. Unfortunately, the position information cannot be easily obtained for indoor navigation, unlike in outdoor navigation cases. In this paper, we propose a method to determine the position based on the magnetic field map matching by using the importance sampling method and multiple magnetic sensors. The proposed method does not simply integrate multiple sensors but uses the normalization and roughness weighting method for outlier mitigation. To implement the indoor pedestrian navigation algorithm more accurately than in existing indoor pedestrian navigation, a 15th-order error model and an importance-sampling extended Kalman filter was utilized to correct the error of the map-matching-aided pedestrian dead reckoning (MAPDR). To verify the performance of the proposed indoor MAPDR algorithm, many experiments were conducted and compared with conventional pedestrian dead reckoning. The experimental results show that the proposed magnetic field MAPDR algorithm provides clear performance improvement in all indoor environments.

Enhancement Of Navigation Technology Using Augmented Reality

Navigation technology has observed a tremendous advancement in the last 10 years with people shifting from using traditional maps to satellite based navigation smartphone apps such as Google maps and Apple maps. These applications mainly focus on outdoor navigation and represent the route in a 2-D layout, which sometimes lacks clarity when it comes to distinguishing between overlapping paths. One more area where this project is focused is indoor navigation. Indoor navigation can be helpful for navigating inside big buildings like hospitals, malls and airports. For example, when a user enters a mall and he or she needs to find a particular showroom, he just needs to put the name of that showroom and he would get 3-D augmented objects on his device which will point to that showroom as he follows the designated path. Augmented reality is used combined with satellite based GPS technology to navigate outdoors as well as indoors. The application uses 3-D markers to point the direction to the user in a real time environment on their devices which will be easy to understand and navigate. At the same time it will augment location based point of interest along the path, which will provide more clarity to the user about his or her environment. From this project we hope to develop a navigation application for users which is easy to use and understand.

Versatile Personal Assistant Dedicated to B/VIP

Today, there are different systems on the market that aim to help Blind or Visually Impaired People (B/VIP) to gain more independency and self-trust. From the classic white cane to various intelligent devices to guide people with vision problems, most of the systems are expensive, difficult to be used or with low efficiency. The subject is a very important one because, according to the World Health Organization, there are approximately 2.2 billion people in the world that have a vision impairment or blindness. Thus, the purpose of this work is to make a short survey on solutions available on the market, in order to develop a low-cost, efficient and easy-to-use system for both indoor and outdoor use. The versatile personal assistant dedicated to B/VIP aims to enhance their independence and also improved outdoor navigation. The smart warning system addressed here is an innovative device aiming to detect obstacles with the help of ultrasonic sensors and warning of their presence by means of a buzzer or vibration. The system, when used outdoor, also gives the possibility to send short message to the B/VIP’s own assistant, in the form of an SMS with the exact location of the B/VIP. Moreover, the SMS’ content can easily create the optimal route to the B/VIP’s location with the Google Maps support for a fast-time assistance.

Low-Cost Open Source Ultrasound-Sensing Based Navigational Support for the Visually Impaired.

Nineteen million Americans have significant vision loss. Over 70% of these are not employed full-time, and more than a quarter live below the poverty line. Globally, there are 36 million blind people, but less than half use white canes or more costly commercial sensory substitutions. The quality of life for visually impaired people is hampered by the resultant lack of independence. To help alleviate these challenges this study reports on the development of a low-cost, open-source ultrasound-based navigational support system in the form of a wearable bracelet to allow people with the lost vision to navigate, orient themselves in their surroundings and avoid obstacles when moving. The system can be largely made with digitally distributed manufacturing using low-cost 3-D printing/milling. It conveys point-distance information by utilizing the natural active sensing approach and modulates measurements into haptic feedback with various vibration patterns within the four-meter range. It does not require complex calibrations and training, consists of the small number of available and inexpensive components, and can be used as an independent addition to traditional tools. Sighted blindfolded participants successfully demonstrated the device for nine primary everyday navigation and guidance tasks including indoor and outdoor navigation and avoiding collisions with other pedestrians.

CAPRIO

Recently, navigation and localization systems have emerged to support queries like the shortest distance in either indoor or outdoor with additional constraints. These systems, however, neither combine the indoor and outdoor information nor consider the external natural conditions like the weather that one may face across an outdoor path. In this demonstration paper we present CAPRIO , which proposes and implements a novel graph representation that integrates indoor and outdoor information to discover paths that personalize outdoor exposure while minimizes the overall path length. We also demonstrate how unifying the graph algorithms for indoor and outdoor navigation enables significant optimizations that would not be possible otherwise.

An ant-inspired celestial compass applied to autonomous outdoor robot navigation

Desert ants use the polarization of skylight and a combination of stride and ventral optic flow integration processes to track the nest and food positions when traveling, achieving outstanding performances. Navigation sensors such as global positioning systems and inertial measurement units still have disadvantages such as their low resolution and drift. Taking our inspiration from ants, we developed a 2-pixel celestial compass which computes the heading angle of a mobile robot in the ultraviolet range. The output signals obtained with this optical compass were investigated under various weather and ultraviolet conditions and compared with those obtained on a magnetometer in the vicinity of our laboratory. After being embedded on-board the robot, the sensor was first used to compensate for random yaw disturbances. We then used the compass to keep the Hexabot robot’s heading angle constant in a straight forward walking task over a flat terrain while its walking movements were imposing yaw disturbances. Experiments performed under various meteorological conditions showed the occurrence of steady state heading angle errors ranging from 0.3∘ (with a clear sky) to 2.9∘ (under changeable sky conditions). The compass was also tested under canopies and showed a strong ability to determine the robot’s heading while most of the sky was hidden by the foliage. Lastly, a waterproof, mono-pixel version of the sensor was designed and successfully tested in a preliminary underwater benchmark test. These results suggest this new optical compass shows great precision and reliability in a wide range of outdoor conditions, which makes it highly suitable for autonomous robotic outdoor navigation tasks. A celestial compass and a minimalistic optic flow sensor called M2APix (based on Michaelis–Menten Auto-adaptive Pixels) were therefore embedded on-board our latest insectoid robot called AntBot, to complete the previously mentioned ant-like homing navigation processes. First the robot was displaced manually and made to return to its starting-point on the basis of its absolute knowledge of the coordinates of this point. Lastly, AntBot was tested in fully autonomous navigation experiments, in which it explored its environment and then returned to base using the same sensory modes as those on which desert ants rely. AntBot produced robust, precise localization performances with a homing error as small as 0.7% of the entire trajectory.

Research on Application of Beacon-based Location Technology in American Universities

With the popularity of smart phones, whether we are driving or walking, we are accustomed to using GPS for outdoor navigation. However, when you are in a library, shopping mall, etc., the GPS signal is blocked and the system will not be able to navigate for you. Then we need a technology that can provide indoor navigation. Beacon is a near-field sensing technology based on low-power Bluetooth technology that can be used to provide indoor positioning services for users with the Bluetooth capabilities of mobile phones. This paper describes the Beacon positioning technology principle and the application of Beacon-based location technology in American universities. In a university library, lab, conference room and other indoor environments, Beacon-based positioning technology can provide specific information transmission, indoor navigation, book recommendation based on big data analysis, and attendance check-in functions.

Micro navigation system for smart parking area

Despite its limited accuracy, navigation systems depending on GPS are currently attracting considerable interest due to their increasing convenience in the field of transportation area. So far, most outdoor navigation applications are using GPS and the absence of a low-cost alternative with acceptable accuracy satisfying the indoor applications requirements has become one of the motivational topics to follow up. Therefore, different studies have been recently conducted in order to develop an accurate indoor localisation system. In this paper, we will propose a micro-navigation system for parking area with a visual positioning system (VPS) based on the surveillance camera network adaptation and the image processing theory. From the data provided by the VPS, a navigation tool will be presented besides. The proposed system has achieved an accuracy error of 0.08 M, and proved a remarkable improvement in terms of finding parking places time consuming. We believe that we have designed an innovative solution responding to traffic jams and pollution issues as well as stress and finding parking places time consuming.

An Indoor and Outdoor Navigation System for Visually Impaired People

In this paper, we present a system that allows visually impaired people to autonomously navigate in an unknown indoor and outdoor environment. The system, explicitly designed for low vision people, can be generalized to other users in an easy way. We assume that special landmarks are posed for helping the users in the localization of pre-defined paths. Our novel approach exploits the use of both the inertial sensors and the camera integrated into the smartphone as sensors. Such a navigation system can also provide direction estimates to the tracking system to the users. The success of out approach is proved both through experimental tests performed in controlled indoor environments and in real outdoor installations. A comparison with deep learning methods has been presented.

Polarized skylight-based heading measurements: a bio-inspired approach.

Many insects such as desert ants, crickets, locusts, dung beetles, bees and monarch butterflies have been found to extract their navigation cues from the regular pattern of the linearly polarized skylight. These species are equipped with ommatidia in the dorsal rim area of their compound eyes, which are sensitive to the angle of polarization of the skylight. In the polarization-based robotic vision, most of the sensors used so far comprise high-definition CCD or CMOS cameras topped with linear polarizers. Here, we present a 2-pixel polarization-sensitive visual sensor, which was strongly inspired by the dorsal rim area of desert ants' compound eyes, designed to determine the direction of polarization of the skylight. The spectral sensitivity of this minimalistic sensor, which requires no lenses, is in the ultraviolet range. Five different methods of computing the direction of polarization were implemented and tested here. Our own methods, the extended and AntBot method, outperformed the other three, giving a mean angular error of only 0.62° ± 0.40° (median: 0.24°) and 0.69° ± 0.52° (median: 0.39°), respectively (mean ± standard deviation). The results obtained in outdoor field studies show that our celestial compass gives excellent results at a very low computational cost, which makes it highly suitable for autonomous outdoor navigation purposes.

Human Activity Monitoring and Recognition of Elderly People with Mild Cognitive Decline

Elderly people suffering from Dementia and Alzheimer meet with a progressive cognitive decline. This make them experience hardship in performing their everyday conventional activities especially in their outdoor navigation as they tend to forget landmarks even in familiar environments due to gradual decline in their memory and thinking abilities. Hence, disorientation and wandering become common issue. Providing assistive guidance to the elderly people in their outdoor mobility has become a challenging task for caretakers and family members as most of the elders prefer to live independently. Thus, there arises a need for efficient solutions that can monitor the elderly people movements and notify the caretakers in the event of disorientation or wandering being detected. The main objective of this paper is to propose one such solution which can support the provision of the best monitoring care in the outdoor navigation by mining through the elder’s historical movement trajectories and detecting outliers if any, in the elder’s current on-going trajectory. Further, the system tries to identify the underlying wandering pattern such as lapping, pacing or random in the outlier that could possibly help in analyzing the effect of medication in the treatment of dementia. Â

Economical High⁻Low Temperature and Heading Rotation Test Method for the Evaluation and Optimization of the Temperature Control System for High-Precision Platform Inertial Navigation Systems.

Inertial navigation systems (INSs) use the temperature control system to ensure the stability of the temperature of the inertial sensors for improving the navigation accuracy of the INSs. That is, the temperature control accuracy affects the performance of the INSs. Thus, the performance of temperature control systems must be evaluated before their application. However, nearly all high-precision INSs are large and heavy and require long-term testing under many different experimental conditions. As a result, conducting an outdoor navigation experiment, which involves high–low temperature and heading rotation tests, is time consuming, laborious, and costly for researchers. To address this issue, an economical high–low temperature and heading rotation test method for high-precision platform INSs is proposed, and an evaluation system based on this method is developed to evaluate the performance of the temperature control systems for high-precision platform INSs indoors. The evaluation system uses an acrylic chamber, exhaust fans, temperature sensors, and an air conditioner to simulate the environment temperature change. The outer gimbals of the platform INSs are utilized to simulate the heading rotation. The temperature control system of a high-precision platform INS is evaluated using the proposed evaluation method. The temperature difference of the gyros is obtained in the high–low temperature test, and the temperature fluctuation of the temperature control system is observed in the rotation test. These tests verify the effectiveness of the proposed evaluation method. Then, the corresponding optimization method for the temperature control system of this high-precision platform INS is put forward on the basis of the test results of the evaluation system. Experimental results show that the maximum temperature differences of the two gyros between high- and low-temperature tests are decreased from 1.51 °C to 0.50 °C, and the maximum temperature fluctuation value of the temperature control system is decreased from 0.81 °C to 0.27 °C after the proposed evaluation and optimization processes. Therefore, the proposed methods are cost effective and useful for evaluating and optimization of the temperature control system for INSs.

Intelligent vision-based navigation system for mobile robot: A technological review

Vision system is gradually becoming more important. As computing technology advances, it has been widely utilized in many industrial and service sectors. One of the critical applications for vision system is to navigate mobile robot safely. In order to do so, several technological elements are required. This article focuses on reviewing recent researches conducted on the intelligent vision-based navigation system for the mobile robot. These include the utilization of mobile robot in various sectors such as manufacturing, warehouse, agriculture, outdoor navigation and other service sectors. Multiple intelligent algorithms used in developing robot vision system were also reviewed.

Usability Evaluation of a Novel Robotic Power Wheelchair for Indoor and Outdoor Navigation

ObjectiveTo compare the Mobility Enhancement roBotic (MEBot) wheelchair’s capabilities with commercial electric-powered wheelchairs (EPWs) by performing a systematic usability evaluation. DesignUsability in effectiveness, efficacy, and satisfaction was evaluated using quantitative measures. A semistructured interview was employed to gather feedback about the users’ interaction with MEBot. SettingLaboratory testing of EPW driving performance with 2 devices in a controlled setting simulating common EPW driving tasks. ParticipantsA convenience sample of expert EPW users (N=12; 9 men, 3 women) with an average age of 54.7±10.9 years and 16.3± 8.1 years of EPW driving experience. InterventionsNot applicable. Main Outcome MeasuresPowered mobility clinical driving assessment (PMCDA), Satisfaction Questionnaire, National Aeronautics and Space Administration’s Task Load Index. ResultsParticipants were able to perform significantly higher number of tasks (P=.004), with significantly higher scores in both the adequacy-efficacy (P=.005) and the safety (P=.005) domains of the PMCDA while using MEBot over curbs and cross-slopes. However, participants reported significantly higher mental demand (P=.005) while using MEBot to navigate curbs and cross-slopes due to MEBot’s complexity to perform its mobility applications which increased user’s cognitive demands. ConclusionsOverall, this usability evaluation demonstrated that MEBot is a promising EPW device to use indoors and outdoors with architectural barriers such as curbs and cross-slopes. Current design limitations were highlighted with recommendations for further improvement.