Energy-Efficient Indoor Search by Swarms of Simulated Flying Robots Without Global Information

Swarms of flying robots are a promising alternative to ground-based robots for search in indoor environments with advantages such as increased speed and the ability to fly above obstacles. However, there are numerous problems that must be surmounted including limitations in available sensory and on-board processing capabilities, and low flight endurance. This paper introduces a novel strategy to coordinate a swarm of flying robots for indoor exploration that significantly increases energy efficiency. The presented algorithm is fully distributed and scalable. It relies solely on local sensing and low-bandwidth communication, and does not require absolute positioning, localisation, or explicit world-models. It assumes that flying robots can temporarily attach to the ceiling, or land on the ground for efficient surveillance over extended periods of time. To further reduce energy consumption, the swarm is incrementally deployed by launching one robot at a time. Extensive simulation experiments demonstrate that increasing the time between consecutive robot launches significantly lowers energy consumption by reducing total swarm flight time, while also decreasing collision probability. As a trade-off, however, the search time increases with increased inter-launch periods. These effects are stronger in more complex environments. The proposed localisation-free strategy provides an energy efficient search behaviour adaptable to different environments or timing constraints

Map-assisted Indoor Positioning Utilizing Ubiquitous WiFi Signals

The demand of indoor positioning solution is on the increase dramatically, and WiFi-based indoor positioning is known as a very promising approach because of the ubiquitous WiFi signals and WiFi-compatible mobile devices. Improving the positioning accuracy is the primary target of most recent works, while the excessive deployment overhead is also a challenging problem behind. In this thesis, the author is investigating the indoor positioning problem from the aspects of indoor map information and the ubiquity of WiFi signals. This thesis proposes a set of novel WiFi positioning schemes to improve the accuracy and efficiency. Firstly, considering the access point (AP) placement is the first step to deploy indoor positioning system using WiFi, an AP placement algorithm is provided to generate the placement of APs in a given indoor environment. The AP placement algorithm utilises the floor plan information from the indoor map, in which the placement of APs is optimised to benefit the fingerprinting- based positioning. Secondly, the patterns of WiFi signals are observed and deeply analysed from sibling and spatial aspects in conjunction with pathway map from indoor map to address the problem of inconsistent WiFi signal observations. The sibling and spatial signal patterns are used to improve both positioning accuracy and efficiency. Thirdly, an AP-centred architecture is proposed by moving the positioning modules from mobile handheld to APs to facilitate the applications where mobile handheld doesn’t directly participate positioning. Meanwhile, the fingerprint technique is adopted into the AP-centred architecture to maintain comparable positioning accuracy. All the proposed works in this thesis are adequately designed, implemented and evaluated in the real-world environment and show improved performance

Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications

[EN] In areas with limited infrastructure, Unmanned Aerial Vehicles (UAVs) can come in handy as relays for car-to-car communications. Since UAVs are able to fully explore a three-dimensional environment while flying, communications that involve them can be affected by the irregularity of the terrains, that in turn can cause path loss by acting as obstacles. Accounting for this phenomenon, we propose a UAV positioning technique that relies on optimization algorithms to improve the support for vehicular communications. Simulation results show that the best position of the UAV can be timely determined considering the dynamic movement of the cars. Our technique takes into account the current flight altitude, the position of the cars on the ground, and the existing flight restrictions.This work was partially supported by the Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018 , Spain, under Grant RTI2018-096384-B-I00, and grant BES-2015-075988, Ayudas para contratos predoctorales 2015.Hadiwardoyo, SA.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Krinkin, K.; Klionskiy, D.; Hernández-Orallo, E.; Manzoni, P. (2020). Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications. Sensors. 20(2):1-18. https://doi.org/10.3390/s20020356S11820

Napredna (edge computing) softverska arhitektura za upravljanje resursima i unutrašnje pozicioniranje

In Part I, this thesis aims to shed light on IoT and edge com-puting systems and accompanying computing and architectural paradigms, their definition, areas of application, and common use-cases, as well as operational, business, economical, social challenges and benefits. It illustrates modern needs and requests in building IoT systems and current State-of-The-Art (SoTA) approaches to designing them. Additionally, it discusses the security and privacy topics of IoT and edge computing systems. It also encompasses research, design, and implementation of an MQTT-based Resource Management Framework for Edge Com-puting systems that handle: resource management, failover detection and handover administration, logical and physical workload balancing and protection, and monitoring of physical and logical system resources designed for a real-world IoT platform. The thesis offers insights into modern requests for such frameworks, current SoTA approaches, and offer a solution in the form of a software framework, with minimal implementation and communication overhead. In Part II, the thesis elaborates on IPS, their definition, deploy-ment types, commonly used positioning techniques, areas of application, and common use-cases, as well as operational, business, economic, social challenges, and benefits. It specifically discusses designing IPS for the typical IoT infrastructure. It offers insights to modern IPS requests, current SoTA in solving them, and under-line original approaches from this thesis. It elaborates on the research, design and authors’ implementation of an IPS for the IoT – Bluetooth LowEnergyMicrolocation Asset Tracking (BLEMAT), including its software engines (collections of software components) for: indoor positioning, occupancy detection, visualization, pattern discovery and prediction, geofencing, movement pattern detection, visualization, discovery and prediction, social dynamics analysis, and indoor floor plan layout detection.Deo I teze ima je za cilj da rasvetli IoT i edge computing računarske sisteme i prateće računarske paradigme softverskih arhitektura, njihovu definiciju, područja primene i slučajeve uobičajene upotrebe, kao i operativne, poslovne, ekonomske, i socijalne izazove i koristi. Teza ilustruje savremene potrebe i zahtevi u izgradnji IoT sistema i najsavremeniji pristupi u njihovom dizajniranju. Raspravlja se o temama bezbednosti i privatnosti u IoT i edge computing računarskim sistemima. Kao još jedan glavni zadatak, teza je obuhvata istraživanje, dizajn i implementaciju softverske arhitekture za upravljanje resursima zasnovanim na MQTT komunikacionom protokolu za edge computing računarske sisteme koja se bavi: upravljanjem resursima, detekcijom prestanka rada upravljačkih algoritama i administracijom primopredaje tj. transporta upravljačkih algoritama, i logičkim i fizičkim balansiranjem i zaštitom radnog opterećenja sistema. Diskutuju se savremeni zahtevi za takve softverske arhitekture, trenutni pristupi. Na kraju, prikazuje se rešenje sa minimalnim troškovima implementacije i  komunikacije. Deo II teze ima za cilj da objasni sisteme za unutrašnje pozicioniranje, njihovu definiciju, vrste primene, najčešće korišćene tehnike pozicioniranja, područja primene i uobičajene slučajeve upotrebe, kao i operativne, poslovne, ekonomske, i socijalne izazove i koristi. Posebno se diskutuje o dizajniranju ovakvih sistema za tipičnu IoT infrastrukturu. Nudi se uvid u savremene zahteve sisteme za unutrašnje pozicioniranje, trenutne pristupe u rešavanju istih, i naglašeni su originalni pristupe iz ove teze. Dalje je fokus na istraživanju, dizajniranju i implementaciji sistema za unutrašnje pozicioniranje (BLEMAT), uključujući njegove softverske podsisteme (kolekcije softverskih komponenti) za: pozicioniranje u zatvorenom prostoru, detekciju zauzeća prostorija, vizualizaciju, otkrivanje i predviđanje obrazaca kretanja, geofencing, vizualizaciju i analizu društvene dinamike i detekciju rasporeda prostorija unutrašnjeg prostora

Distance Measurement-Based Cooperative Source Localization: A Convex Range-Free Approach

One of the most essential objectives in WSNs is to determine the spatial coordinates of a source or a sensor node having information. In this study, the problem of range measurement-based localization of a signal source or a sensor is revisited. The main challenge of the problem results from the non-convexity associated with range measurements calculated using the distances from the set of nodes with known positions to a xed sen- sor node. Such measurements corresponding to certain distances are non-convex in two and three dimensions. Attempts recently proposed in the literature to eliminate the non- convexity approach the problem as a non-convex geometric minimization problem, using techniques to handle the non-convexity. This study proposes a new fuzzy range-free sensor localization method. The method suggests using some notions of Euclidean geometry to convert the problem into a convex geometric problem. The convex equivalent problem is built using convex fuzzy sets, thus avoiding multiple stable local minima issues, then a gradient based localization algorithm is chosen to solve the problem. Next, the proposed algorithm is simulated considering various scenarios, including the number of available source nodes, fuzzi cation level, and area coverage. The results are compared with an algorithm having similar fuzzy logic settings. Also, the behaviour of both algorithms with noisy measurements are discussed. Finally, future extensions of the algorithm are suggested, along with some guidelines

Building Evacuation with Mobile Devices

In der Dissertation wird ein Konzept für ein Gebäudeevakuierungssystem vorgestellt, das es ermöglicht, Personen mit Hilfe mobiler Endgeräte im Evakuierungsfall aus einem Gebäude zu führen. Die Dissertation gliedert sich in drei thematische Bereiche, in denen zunächst ein Konzept für die Systemarchitektur vorgestellt wird und anschließend verschiedene Algorithmen zur Routenplanung sowie zur Lokalisierung der Geräte vorgestellt und evaluiert werden

Cultural heritage visits supported on visitors' preferences and mobile devices

Monuments, museums and cities are great places to feel and experience neat and interesting things. But cultural heritage is experienced differently by different visitors. The more erudite may know beforehand what they intend to explore, while the least literate usually know and are capable of expressing some of their preferences but do not exactly realize what to see and explore. This paper proposes the use of a mobile application to set an itinerary where you can move at your own pace and, at the same time, have all the complementary information you need about each of the points of interest. The application is designed in face of an adaptive user interface where the routing and augmented reality are connected to acknowledge the needs of different user categories, such as elders, kids, experts or general usersPortuguese Foundation for Science and Technology (FCT)Portuguese Foundation for Science and Technology [UID/EEA/50009/2013, UID/SOC/04020/2013]CRESC ALGARVE 2020, PORTUGAL 2020 [3322]FEDER European Commissioninfo:eu-repo/semantics/publishedVersio

Application of Integer Programming for Mine Evacuation Modeling with Multiple Transportation Modes

The safe evacuation of miners during an emergency within the shortest possible time is very important for the success of a mine evacuation program. Despite developments in the field of mine evacuation, little research has been done on the use of mine vehicles during evacuation. Current research into mine evacuation has emphasized on miner evacuation by foot. Mathematical formulations such as Minimum Cost Network Flow (MCNF) models, Ant Colony algorithms, and shortest path algorithms including Dijkstra's algorithm and Floyd-Warshall algorithm have been used to achieve this. These models, which concentrate on determining the shortest escape routes during evacuation, have been found to be computationally expensive with expanding problem sizes and parameter ranges or they may not offer the best possible solutions.An ideal evacuation route for each miner must be determined considering the available mine vehicles, locations of miners, safe havens such as refuge chambers, and fresh-air bases. This research sought to minimize the total evacuation cost as a function of the evacuation time required during an emergency while simultaneously helping to reduce the risk of exposure of the miners to harmful conditions during the evacuation by leveraging the use of available mine vehicles. A case study on the Turquoise Ridge Underground Mine (Nevada Gold Mines) was conducted to validate the Integer Programming (IP) model. Statistical analysis of the IP model in comparison with a benchmark MCNF model proved that leveraging the use of mine vehicles during an emergency can further reduce the total evacuation time. A cost-savings analysis was made for the IP model, and it was found that the time saved during evacuation, by utilizing the IP model, increased linearly, with an increase in the number of miners present at the time of evacuation

Navigation, Path Planning, and Task Allocation Framework For Mobile Co-Robotic Service Applications in Indoor Building Environments

Recent advances in computing and robotics offer significant potential for improved autonomy in the operation and utilization of today’s buildings. Examples of such building environment functions that could be improved through automation include: a) building performance monitoring for real-time system control and long-term asset management; and b) assisted indoor navigation for improved accessibility and wayfinding. To enable such autonomy, algorithms related to task allocation, path planning, and navigation are required as fundamental technical capabilities. Existing algorithms in these domains have primarily been developed for outdoor environments. However, key technical challenges that prevent the adoption of such algorithms to indoor environments include: a) the inability of the widely adopted outdoor positioning method (Global Positioning System - GPS) to work indoors; and b) the incompleteness of graph networks formed based on indoor environments due to physical access constraints not encountered outdoors. The objective of this dissertation is to develop general and scalable task allocation, path planning, and navigation algorithms for indoor mobile co-robots that are immune to the aforementioned challenges. The primary contributions of this research are: a) route planning and task allocation algorithms for centrally-located mobile co-robots charged with spatiotemporal tasks in arbitrary built environments; b) path planning algorithms that take preferential and pragmatic constraints (e.g., wheelchair ramps) into consideration to determine optimal accessible paths in building environments; and c) navigation and drift correction algorithms for autonomous mobile robotic data collection in buildings. The developed methods and the resulting computational framework have been validated through several simulated experiments and physical deployments in real building environments. Specifically, a scenario analysis is conducted to compare the performance of existing outdoor methods with the developed approach for indoor multi-robotic task allocation and route planning. A simulated case study is performed along with a pilot experiment in an indoor built environment to test the efficiency of the path planning algorithm and the performance of the assisted navigation interface developed considering people with physical disabilities (i.e., wheelchair users) as building occupants and visitors. Furthermore, a case study is performed to demonstrate the informed retrofit decision-making process with the help of data collected by an intelligent multi-sensor fused robot that is subsequently used in an EnergyPlus simulation. The results demonstrate the feasibility of the proposed methods in a range of applications involving constraints on both the environment (e.g., path obstructions) and robot capabilities (e.g., maximum travel distance on a single charge). By focusing on the technical capabilities required for safe and efficient indoor robot operation, this dissertation contributes to the fundamental science that will make mobile co-robots ubiquitous in building environments in the near future.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143969/1/baddu_1.pd