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\chapter{Introduction}\label{Introduction}

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\par This Chapter provides a general background of the role of Global Navigation Satellite System (GNSS) in service robotics, its implementations and challenges. The objectives and contributions of the thesis is presented next and at the end, the outline of the thesis is presented. 

%%%%% SECTION 1.1 BACKGROUND %%%%%
\section{Background}

\par It is fair to say service robotics is a booming industry and it was predicted that in 2020 over half of the expected 1 million+ net robot sales will be from the service robotics industry. The market of service robots is also growing faster than that for industrial robots \cite{deloitte2020} and was expected to generate more than 16 billion US dollars in revenue in 2020. Next-generation robots, including collaborative and service robots, are projected to account for two-thirds of unit robot sales by 2025, up from 22 percent in 2015 \cite{outlook2017}. The expected impact of robots on our future economies is staggering and experts at McKinsey Global Institute estimate that around half of today's work activities could be automated by 2055 \cite{manyika2017future}. Amongst it, the global precision farming market is expected to grow at a compound annual growth rate of 13.1 percent from 2021 to 2028 to reach USD 16.35 billion by 2028 \cite{tmcnet2021}, where robotics and automation play a vital role \cite{de2013precision}.

\par GNSS, being the modern absolute positioning system is a crucial component of agricultural service robots and nearly all robots designed for outdoor operations, except planetary rovers incorporate some sort of global navigation, and the trend has been moving upward since the cancelation of selective availability in 2000 \cite{rovira2015role}. The growing importance and interest in GNSS for agricultural applications has motivated the development of an ISO standard (ISO 12188-1:2010) provides a procedure for evaluating and reporting the accuracy of navigation data determined using positioning devices that are based on GPS, GLONASS, Galileo or similar global navigation satellite systems (GNSS) \cite{iso2010}. GNSS information although easy to access, however has limitations in agricultural environments with difficulties in guaranteeing long term robust and reliable measurements, especially for crucial dynamic states such as heading and speed. Therefore farm robots are endowed with multiple sensors and complicated architectures in such a way that the navigation algorithms embedded in the robot always make an optimized use of available data in real time.



%%%%% SECTION 1.2 OBJECTIVES and CONTRIBUTIONS OF THE THESIS %%%%%
\section{Objectives and contributions of the thesis}\label{Objectives}

\par The role of unmanned vehicles in precision agriculture has expanded manifold and is an active general field of research today \cite{von2013multispectral,zhang2012application, milioto2018real}. Unmanned Ground Vehicles (UGVs) typically deal with cultivation tasks such as seeding, spraying, fertilizing, etc. \cite{biber2012navigation}, and Unmanned Aerial Vehicles (UAVs) take roles such as aerial mapping and crop monitoring \cite{pradeep2018trajectory}. Navigation and localization capabilities of such vehicles are vital to their operations and GNSS form the core of many navigation systems in outdoor agricultural activities. GNSS-based navigation in UGVs could be affected by bad satellites visibility \cite{del2014comparison,d2013satellite} and impaired signal reception, especially when they operate in harsh environments (i.e. foliage, ditches, etc.). These issues are generally mitigated exploiting multiple sensors integration strategies \cite{yoon2007navigation}, robust GNSS receivers and external aiding \cite{saleem2015integration,kurdi2018proposed} at the price of steeper costs and complicated set-ups. In limiting conditions (urban canyons, foliage covers, forests) with low-cost devices, integrating Inertial Navigation Sensors (INS) with GNSS can be challenging due to incorrect modelling of the dynamics of the object itself \cite{cherif2018loosely,remondi1984using}. 

\par Hence targeting a low-cost navigation solution is challenging, yet vital to bringing down costs of UGV implementations in precision agriculture. The overbearing objective of the thesis has been to contribute towards this challenge utilizing recent technological advances in GNSS and communications. This has led the direction of the research towards Android\textsuperscript{\texttrademark} smartphones since Android\textsuperscript{\texttrademark} natively support both on-board ultra-low cost GNSS units and communication interfaces through specific Application Program Interfaces (APIs). 

\par A blue print was provided in \cite{tabarracci2013blueprint} for developing an Android\textsuperscript{\texttrademark} smartphone based Auto-pilot and the differences between a traditional and smartphone based sensors at that time were laid out. In later research \cite{bryant2015autonomous}, an experimental Android\textsuperscript{\texttrademark} smartphone based autopilot platform has been implemented by using smartphone sensors while achieving performances comparable to off-the-shelf autopilots. Some conclusions from their flight tests were landing positional errors being in tens of meters and the potential of using cellular communication to modernize the UAV landscape. The latter aspect is demonstrated in \cite{solidakis2017arduino,zhu2015research,abdelhamid2015development} showing efficient performance of modern cellular networks in UAV communication and control. Better positional performances are achieved in \cite{aldrovandi2015smartphone}, however with GNSS-IMU integration. In the last decades Collaborative Positioning (CP) has constituted a relevant topic in robotics, starting from a set of pioneering research works \cite{1668252,1067998} up to recent paradigms including GNSS, proprioceptive and exteroceptive sensors. The availability of a GNSS receiver, and of a communication subsystem makes smartphones suitable for research on the topic and consolidated methods based on exchange of GNSS measurements can be implemented. Further, newer devices allows to obtain higher quality measurements thanks to improving GNSS chipsets with support to dual frequency and multi-constellation GNSS signals, thus reducing the generic performance gap between high-grade commercial and mass-market receivers.

\par In the general scheme of a positioning unit which is typically interfaced to an application layer, the position information is exchanged to other services or stored in remote databases. Such an architecture is prone to a wide range of RF interference attacks, especially if it is based on products which are low cost, commercially available and off-the-shelf (COTS). Current GNSS signals used for mass-market applications (e.g. GPS L1 C/A, E1 Galileo and GLONASS) do not provide any means to ensure the authenticity of the transmitting source or to protect the receiver against possible spoofing attacks \cite{galileo2008galileo,glonass2002global,ICD-705D}, using standard unencrypted communication services. In the near future, GPS Chips-Message Robust
Authentication (Chimera) \cite{anderson2017chips} and Galileo Open Service Navigation Message Authentication (OSNMA) \cite{fernandez2018galileo} services will allows receivers to be resilient against counterfeit signals with both proposed to be fully operational by the end of 2022 \cite{cameron2019afrl,fernandez2018galileo}. Chimera is a combination of Navigation Message Authentication (NMA) and spreading code encryption in the L1C GPS signal while the Galileo open service OSNMA consists only of the NMA digital signature of the navigation data. However it is still vital to examine the potential effects of intentional interference on the low-cost GNSS units embedded in mass market receivers as well as assessing the resilience of the receiver itself.

\par The main contributions of the thesis are summarized as follows: 
\begin{itemize}
	\item It provides the results of the first documented analysis of Android GNSS raw measurements under a completely controlled environment to separate the contribution of the hardware components and signals reception quality in Android smartphones.
	\item It presents a novel approach of use of GNSS receivers' master-rover relationship constraints to improve position and velocity solutions, through their baseline length and relative velocities computed directly through carrier phase measurements.
	\item  It validates the use of raw GNSS measurements for collaborative relative ranging between GNSS receivers when compared to stand alone positioning based solutions. Successful data exchange of raw GNSS measurements is carried out through the IEEE802.11b Wi-Fi connection in Android smartphones. This paradigm is exploited to collaboratively improve the accuracy in the position estimation of a UGV in a UAV-UGV outdoor setup.
	\item The effects of anthropogenic disturbances on the GNSS units integrated in different grade drones and Android smartphones is analysed, specifically on positioning and raw measurements.
\end{itemize}

\par Some of the works presented in the thesis were published in peer-reviewed journal papers \cite{Gogoi_2018,gogoi2018fast,manzino2018assessment} and in different international conferences \cite{Gogoi_2019,gogoi2020proof, rustamov2020gnss,rustamov2020assessment}. Furthermore, the work done in Section \ref{GNSS_Collaborative_Ranging} and Section \ref{Proof_of_Concept} represents some of the fundamentals of the CAPS-Loc idea which won the Italy regional first prize in the 2019 GSA Galileo Masters Competition and was in the top 10 of global finalists.

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\section{Outline of the thesis}
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\par  \textbf{Chapter \ref{Title_Navigation_in_Service_Robotics}} introduces service robotics and outlines its importance to the modern world. With focus on outdoor unmanned  vehicles, the navigational technologies widely used are explained. The current challenges to robust and low cost GNSS based navigation in UAVs and UGVs are explained thereafter. The approach taken in the thesis towards collaborative positioning solutions and the use of Android smartphones to represent COTS GNSS receivers is discussed.

\par \textbf{Chapter \ref{GlobalNavigationSatelliteSystems}} provides an overview of the fundamentals of GNSS with GNSS signals, GNSS receivers and the standard GNSS positioning algorithm explained in some detail. A brief overview of GNSS errors is provided at the end.

\par \textbf{Chapter \ref{AndroidSmartpohnes_Based_GNSS}} provides the analysis of Android GNSS raw measurements through tests carried out in a real environment and in a controlled environment anechoic chamber using different Android models. In addition, signal processing techniques employed aiming at increasing accuracy and precision of positioning solutions are presented.

\par \textbf{Chapter \ref{Collaborative_GNSS_Methodology_and_Application}} details the different collaborative GNSS approaches explored to be applicable to a service robotics scenario with low cost GNSS receivers and the results are seen. Firstly, a fast deformation monitoring analysis through single differenced, time differenced GNSS raw measurements with low cost mass market receivers is presented. Secondly, the experimental validation of a collaborative relaitve ranging technique based on the exchange of raw GNSS measurements between Android smartphones is presented. The investigation of utilizing the relative ranging to the positioning solution of an UGV in a UAV-UGV cooperative paradigm is presented at the end.

\par \textbf{Chapter \ref{InterferenceThreats}} looks at the interference threats to GNSS in service robotics. The effects of anthropogenic disturbances, RF jamming and spoofing on the GNSS units integrated in different grade drones and smartphones is seen. Further, possible security threats to the proposed cooperative framework presented in this thesis is discussed along with an analysis on how cooperative positioning could help in the defense against RF attacks.

\par \textbf{Chapter \ref{Conclusions}} provides the summary of the research work presented within this thesis and discusses some future works. 

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