Physics-Based Swarm Intelligence for Disaster Relief Communications

This study explores how a swarm of aerial mobile vehicles can provide network connectivity and meet the stringent requirements of public protection and disaster relief operations. In this context, we design a physics-based controlled mobility strategy, which we name the extended Virtual Force Protocol (VFPe), allowing self-propelled nodes, and in particular here unmanned aerial vehicles, to fly autonomously and cooperatively. In this way, ground devices scattered on the operation site may establish communications through the wireless multi-hop communication routes formed by the network of aerial nodes. We further investigate through simulations the behavior of the VFPe protocol, notably focusing on the way node location information is disseminated into the network as well as on the impact of the number of exploration nodes on the overall network performance.Comment: in International Conference on Ad Hoc Networks and Wireless, Jul 2016, Lille, Franc

Design and development of an unmanned aerial and ground vehicles for precision pesticide spraying

Günümüzde, bitki hastalıkları tarımsal üretimi etkileyen önemli sorunlardan birisi olarak karşımıza çıkmaktadır. Bitkileri hastalıklardan ve zararlı otların etkilerinden korumak hem tarımda üretimi artırmak hem de tarımın kalitesini yükseltmek için büyük önem taşımaktadır. Tarımsal ürünler, ülkemizde ve dünyada çeşitli ilaçlama yöntemleri kullanılarak korunabilmektedir. Bu yöntemlerin başında gelen ilaçlama yolu ile bitki koruma yöntemi üretimin kalitesini geliştirmek ve rekolteyi artırmak amacıyla yaygın olarak kullanılmaktadır. Ancak bitkilerin korunmasında uygulanan geleneksel ilaçlama yöntemlerinin bitkilere ve toprağa büyük ölçüde zarar verdiği gözlenmektedir. Son yıllarda gelişmiş ülkelerdeki tarımsal uygulamalarda robotların kullanımı hızla artmakta, tarımsal alanlarda özellikle uzaktan algılama ve hassas tarım çalışmalarında bu robotların kullanıldığı görülmektedir. Dahası, tarımsal üretimde yararlanılan fayda-maliyet oranı da dikkate alındığında, günümüzde hassas tarım uygulamalarında robotların kullanılmasının kaçınılmaz hale geldiği anlaşılmaktadır. Günümüz gereksinimleri ve gelişen teknoloji göz önüne alınarak planlanmış olan bu çalışmada, ülkemizde yaygın olarak kullanılan tarımsal mücadele yöntemlerinin maliyetlerini, tarımsal üretimin miktarını ve kalitesini önemli ölçüde etkileyecek geleneksel ilaçlama yöntemlerine alternatif olabilecek bir tarımsal mücadele sistemi geliştirilmiştir. Çalışmada, yakın mesafeden doğrudan hedeflenen bitki üzerine ilaçlama yapılması, ilaçlama sırasında toprağa ve bitkilere verilen zararın en aza indirgenmesi hedeflenmiştir. Bu doğrultuda, özgün tasarım multispektral kamera, ilaçlama ünitesi, Yer Kontrol İstasyonu (YKİ) ve eşgüdümlü çalışabilen İnsansız Hava Aracı (İHA) ile İnsansız Yer Aracından (İYA) oluşan tarımsal mücadele mekanizması tasarlanmış ve geliştirilmiştir. Bu mekanizma, tarımsal ilaçlama uygulamaları için geleneksel yöntemlere kıyasla daha ileri düzey bir alternatif yöntem olarak ortaya çıkmaktadır.TABLE OF CONTENTS ÖZET ................................................................................................................ vii ABSTRACT ....................................................................................................... ix ACKNOWLEDGEMENTS ................................................................................ xi 1 . INTRODUCTION .......................................................................................... 1 2. LITERATURE REVIEW ............................................................................. 6 2.1 Robotics ..................................................................................................... 9 2.2 Unmanned Ground Vehicles ..................................................................... 11 2.3 Unmanned Aerial Vehicles ....................................................................... 11 2.4 Remote Sensing Technology .................................................................... 17 2.4.1 Remote Sensing Platforms ................................................................. 19 2.4.2 Plant Disease Detection ..................................................................... 22 2.4.3 Normalized Difference Vegetation Index ........................................... 27 3 . MATERIAL AND METHOD ....................................................................... 29 3.1 Ground Control Station ............................................................................ 32 3.2 Unmanned Ground Vehicle ...................................................................... 37 3.2.1 Specifications of the UGV ................................................................. 38 3.2.2 The Chassis and Sensor Holder .......................................................... 40 3.2.3 FEM Analysis .................................................................................... 43 3.3 Multispectral Camera for Plant Disease Detection .................................... 44 3.3.1 Spectral Imaging ................................................................................ 46 3.3.2 Multispectral Camera – Spektra TSL128RN ...................................... 47 3.3.3 The hardware of the Device ............................................................... 49 3.3.4 Calibrating Steps of the Device .......................................................... 52 3.3.5 Software for the Device ..................................................................... 56 3.3.6 Measurements using NDVI Devices .................................................. 58 3.4 Unmanned Aerial Vehicle ........................................................................ 62 3.4.1 The Chassis and Arm ......................................................................... 66 3.4.2 FEM Analysis ................................................................................... 69 3.4.3 Modal Analysis ................................................................................. 70 3.4.4 Performance of the Propellers ............................................................ 73 3.4.5 Flight Duration and Maximum Conditions ......................................... 82 3.4.6 Strain Measurement ........................................................................... 84 3.4.7 Other Parts ........................................................................................ 92 3.4.8 Specifications of the UAV ................................................................. 95 3.4.9 Flight Tests ....................................................................................... 96 3.5 Spraying Unit –Sprayer and Tank ............................................................. 99 4 . RESULTS AND DISCUSSION .................................................................. 103 4.1 The UGV ............................................................................................... 103 4.2 The Multispectral Camera ...................................................................... 105 4.3 The UAV ............................................................................................... 115 4.4 The Sprayer............................................................................................ 135 xv 4.5 UGV and Multispectral Camera .............................................................. 138 4.6 Aerial Spraying UAV ............................................................................. 145 5 . CONCLUSIONS......................................................................................... 154 REFERENCES ................................................................................................ 156 RESUME......................................................................................................... 16

Task-based agricultural mobile robots in arable farming: A review

In agriculture (in the context of this paper, the terms “agriculture” and “farming” refer to only the farming of crops and exclude the farming of animals), smart farming and automated agricultural technology have emerged as promising methodologies for increasing the crop productivity without sacrificing produce quality. The emergence of various robotics technologies has facilitated the application of these techniques in agricultural processes. However, incorporating this technology in farms has proven to be challenging because of the large variations in shape, size, rate and type of growth, type of produce, and environmental requirements for different types of crops. Agricultural processes are chains of systematic, repetitive, and time-dependent tasks. However, some agricultural processes differ based on the type of farming, namely permanent crop farming and arable farming. Permanent crop farming includes permanent crops or woody plants such as orchards and vineyards whereas arable farming includes temporary crops such as wheat and rice. Major operations in open arable farming include tilling, soil analysis, seeding, transplanting, crop scouting, pest control, weed removal and harvesting where robots can assist in performing all of these tasks. Each specific operation requires axillary devices and sensors with specific functions. This article reviews the latest advances in the application of mobile robots in these agricultural operations for open arable farming and provide an overview of the systems and techniques that are used. This article also discusses various challenges for future improvements in using reliable mobile robots for arable farmin

A review on the prospects of mobile manipulators for smart maintenance of railway track

Inspection and repair interventions play vital roles in the asset management of railways. Autonomous mobile manipulators possess considerable potential to replace humans in many hazardous railway track maintenance tasks with high efficiency. This paper investigates the prospects of the use of mobile manipulators in track maintenance tasks. The current state of railway track inspection and repair technologies is initially reviewed, revealing that very few mobile manipulators are in the railways. Of note, the technologies are analytically scrutinized to ascertain advantages, unique capabilities, and potential use in the deployment of mobile manipulators for inspection and repair tasks across various industries. Most mobile manipulators in maintenance use ground robots, while other applications use aerial, underwater, or space robots. Power transmission lines, the nuclear industry, and space are the most extensive application areas. Clearly, the railways infrastructure managers can benefit from the adaptation of best practices from these diversified designs and their broad deployment, leading to enhanced human safety and optimized asset digitalization. A case study is presented to show the potential use of mobile manipulators in railway track maintenance tasks. Moreover, the benefits of the mobile manipulator are discussed based on previous research. Finally, challenges and requirements are reviewed to provide insights into future research

Biologically inspired herding of animal groups by robots

A single sheepdog can bring together and manoeuvre hundreds of sheep from one location to another. Engineers and ecologists are fascinated by this sheepdog herding because of the potential it provides for ‘bio-herding’: a biologically inspired herding of animal groups by robots. Although many herding algorithms have been proposed, most are studied via simulation.There are a variety of ecological problems where management of wild animal groups is currently impossible, dangerous and/or costly for humans to manage directly, and which may benefit from bio-herding solutions.Unmanned aerial vehicles (UAVs) now deliver significant benefits to the economy and society. Here, we suggest the use of UAVs for bio-herding. Given their mobility and speed, UAVs can be used in a wide range of environments and interact with animal groups at sea, over the land and in the air.We present a potential roadmap for achieving bio-herding using a pair of UAVs. In our framework, one UAV performs ‘surveillance’ of animal groups, informing the movement of a second UAV that herds them. We highlight the promise and flexibility of a paired UAV approach while emphasising its practical and ethical challenges. We start by describing the types of experiments and data required to understand individual and collective responses to UAVs. Next, we describe how to develop appropriate herding algorithms. Finally, we describe the integration of bio-herding algorithms into software and hardware architecture

The Future of Blackbird Management Research

Human society values birds for their intrinsic and aesthetic value as well as the ecosystem services they provide as pollinators, consumers of pests, and distributors of nutrients and seeds (Wenny et al. 2011). At the same time, conflict between birds and humans is an age-old phenomenon that has persisted as society has transformed and the scale of agriculture has expanded (Conover 2002). Managing conflict between birds and agriculture is challenging for many reasons. Foremost, the need to consider both human welfare and conservation of protected bird species is paramount, with nonlethal management methods preferred to lethal measures from societal, economical, and ecological standpoints (Miller 2007; Linz et al. 2015). Second, methods must be effective, practical, and economical for agricultural implementation. Finally, management methods must overcome characteristics that make birds difficult to manage including uncertainty in population estimates, fecundity, mobility, and adaptive behaviors. All challenges are compounded when attempting to establish management methods that fit within modern agricultural practices, while simultaneously supporting conservation efforts to protect wildlife. Labor-saving devices and methodologies resulting from agricultural advances in mechanical, chemical, genetic, and information technologies have facilitated a shift to larger crop fields, a broader range of suitable habitat for a variety of crops, and consolidated farms in North America (MacDonald et al. 20(3). This shift to large. less labor-intensive farms has supported the ability to feed an ever-increasing human population but has complicated the relationship between humans and wildlife. Modern agriculture directly impacts wildlife by altering natural habitat. resulting in the increase of species able to thrive in agricultural landscapes and the decline of species unable to adapt. Thus. agriculture often provides increased carrying capacity for species responsible for agricultural damage (Van Vuren and Smallwood 1996). However, changes in harvest efficiency have resulted in less crop waste and reduced availability of high-energy foods available to birds postharvest, potentially placing common farmland birds at risk of decline (Krapu et al. 2004; Galle et al. 2009). Nevertheless, vertebrate species able to adapt to the agricultural landscape often reach pest levels, resulting in producers seeking tools to reduce damage, tools that have not necessarily advanced in concert with modern agriculture. Red-winged blackbirds (150 million; Agelaius phoeniceus), brown-headed cowbirds (120 million; Molothrus ater), common grackles (69 million; Quiscalus quiscula), and yellowheaded blackbirds (15 million; Xanthocephalus xanthocephalus) are among the most numerous birds in North America (Rosenberg et al. 2016). This book has identified conflicts between blackbirds and agricultural commodity groups including livestock, rice, corn, sunflower, and numerous specialty crops (Dolbeer 1990; Cummings et al. 2005; Anderson et al. 2013; Klosterman et al. 2013; Figure 13.1). Continued progress in development of blackbird management methods and acquisition of baseline knowledge as to its impacts on blackbird populations are needed at local, regional, and national scales. In this chapter, I evaluate gaps in knowledge and potential research directions. I address the following topics: (I) blackbird biology at the species, population, and community levels; (2) the influence of changing landscapes on blackbirds and agricultural damage in terms of agricultural practices, habitat, and climate change; (3) the limitations of lethal and nonlethal management tools (i.e., repellents, frightening devices, and evading strategies) and how research can optimize techniques or facilitate new tool discovery; and (4) economic evaluation of management and human dimensions

DRONE AMERICA: THE END OF PRIVACY?

Cutting-edge technological innovations have enabled law enforcement agencies to collect data over a geographical area in relatively short amounts of time. Drones (also known as unmanned aerial vehicles) are becoming increasingly acceptable and employed by state and local law enforcement to become force multipliers. While the Federal Aviation Administration has addressed the integration and safety of flight requirements for law enforcement agencies to utilize drones, federal privacy and data collection regulations are unresolved. This thesis argues that federal regulation is required and attempts to highlight the distinction between surveillance technology and delivery platforms to understand how to approach the regulation of data gathering. In doing so, this thesis uses a political, economic, socio-cultural, and technological (PEST) analysis to examine Title III and relative jurisprudence dealing with both surveillance and aerial platforms. The PEST analysis aims to bring forward the salient points in crafting recommendations and expansion in current legislation that support an increase in citizens’ safety and security, but remain within the bounds of constitutional liberty and the Fourth Amendment.Lieutenant Commander, United States NavyApproved for public release. distribution is unlimite