Aerial Robotics

The Solar-Powered Autonomous Quadcopter (SPAQ) is a standalone autonomous surveillance system designed to carry out intelligently the capturing of video data from remote locations. Analytically, the SPAQ comprises four units: the solar power system, the autonomous navigation system, the flight control system and the surveillance system. Appropriate designs were made for the constituent parts of the SPAQ system with full implementation carried out on the surveillance system using a Raspberry Pi Single Board Computer (SBC). The SBC was connected first to a camera onboard the quadcopter, and then to a base station for viewing the video feed through a Wi-Fi network. The inclusive hardware segment of the SPAQ was achieved with the modular system design approach. The incorporated on-board solar power system is designed to extend the flight time for the SPAQ in order to suit time-tasking applications.

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of AI. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a 'good AI society'. To do so, we examine how each report addresses the following three topics: (a) the development of a 'good AI society'; (b) the role and responsibility of the government, the private sector, and the research community (including academia) in pursuing such a development; and (c) where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a 'good AI society'. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach.

Unmanned Aerial Vehicles (UAVs) are versatile machines that can be used in a variety of applications, such as automatic monitoring of crops and water channels, pest detection, animal counting etc. Autonomous flying is a desirable feature for UAVs, especially for those that are frequently used in monitoring and inspection of large areas. In some situations, global positioning system signal is not guaranteed or its error might be too large, hence other methods of local position feedback are required. In such a context, we present the development of a vision-based line following strategy for an autonomous UAV. The proposed system is intended to guide an autonomous UAV to follow water channel margins, crop lines and other similar patterns, to support automatic monitoring and inspection activities. We present the design of a nonlinear path following controller and we show that the resulting closed-loop system is stable in the sense of Lyapunov. We also propose a visual-based line detection algorithm that it is capable of detecting the average position and orientation of the main lines on the image frames captured by the UAV downwards facing camera. Finally, we present and discuss some experimental results that show the good performance of the proposed system.

— To simplify the usage of the Unmanned Aerial Systems (UAS), extending their use to a great number of applications, fully autonomous operation is needed. There are many open-source architecture frameworks for UAS that claim the autonomous operation of UAS, but they still have two main open issues: (1) level of autonomy, being in most of the cases limited and (2) versatility, being most of them designed specifically for some applications or aerial platforms. As a response to these needs and issues, this paper presents Aerostack, a system architecture and open-source multipurpose software framework for autonomous multi-UAS operation. To provide higher degrees of autonomy, Aerostack's system architecture integrates state of the art concepts of intelligent, cognitive and social robotics, based on five layers: reactive, executive, deliberative, reflective, and social. To be a highly versatile practical solution, Aerostack's open-source software framework includes the main components to execute the architecture for fully autonomous missions of swarms of UAS; a collection of ready-to-use and flight proven modular components that can be reused by the users and developers; and compatibility with five well known aerial platforms, as well as a high number of sensors. Aerostack has been validated during three years by its successful use on many research projects, international competitions and exhibitions. To corroborate this fact, this paper also presents Aerostack carrying out a fictional fully autonomous indoors search and rescue mission.

We would like to invite you to join this exciting new project as a chapter contributor on one of the topics listed below. Since this is a textbook, a great deal of this chapter entails a survey on the topic under the paradigm of cyber-physical systems, what can be done onboard and remotely, the distributed nature of the system and some exercises on futurology (anticipating trends can shed some light on upcoming designs). IET will bring great visibility to your work. Each chapter should be around 20-25 pages each and can be submitted as a Word or Latex File. The IET will send you additional info (formatting, permission form, etc.) with the contributor's agreement once you have decided to contribute to the book. Visit http://www.theiet.org/resources/author-hub/books/index.cfm to get all contributor's information to an IET research-level book. Each book is expected to have a total number of 500 printed pages (with approximately 550 words per page and a 20% allowance for figures and tables). We have included a tentative schedule and list of topics below. If this is something you would consider, please send us the title of your chapter, a short description/abstract of the chapter content, and your full contact details. We will expect original content and new insights for this book. You can, of course, reuse published material but the percentage of material reuse for the chapter should be less than 40%. The IET will run a piracy software on the full manuscript to control that you are including original material and will reject chapters who contain a large amount of already-published material so please do take this into consideration. We would appreciate your feedback by December 31, 2017. Please do not hesitate to contact us if you have any queries. We look forward to working with you towards the successful publication.

— In this paper a scalable and flexible Architecture for real-time mission planning and dynamic agent-to-task assignment for a swarm of Unmanned Aerial Vehicles (UAV) is presented. The proposed mission planning architecture consists of a Global Mission Planner (GMP) which is responsible of assigning and monitoring different high-level missions through an Agent Mission Planner (AMP), which is in charge of providing and monitoring each task of the mission to each UAV in the swarm. The objective of the proposed architecture is to carry out high-level missions such as autonomous multi-agent exploration, automatic target detection and recognition, search and rescue, and other different missions with the ability of dynamically re-adapt the mission in real-time. The proposed architecture has been evaluated in simulation and real indoor flights demonstrating its robustness in different scenarios and its flexibility for real-time mission re-planning and dynamic agent-to-task assignment.

— Personal drones are becoming part of every day life. To fully integrate them into society, it is crucial to design safe and intuitive ways to interact with these aerial systems. The recent advances on User-Centered Design (UCD) applied to Natural User Interfaces (NUIs) intend to make use of human innate features, such as speech, gestures and vision to interact with technology in the way humans would with one another. In this paper, a Graphical User Interface (GUI) and several NUI methods are studied and implemented, along with computer vision techniques, in a single software framework for aerial robotics called Aerostack which allows for intuitive and natural human-quadrotor interaction in indoor GPS-denied environments. These strategies include speech, body position, hand gesture and visual marker interactions used to directly command tasks to the drone. The NUIs presented are based on devices like the Leap Motion Controller, microphones and small size monocular on-board cameras which are unnoticeable to the user. Thanks to this UCD perspective, the users can choose the most intuitive and effective type of interaction for their application. Additionally, the strategies proposed allow for multi-modal interaction between multiple users and the drone by being able to integrate several of these interfaces in one single application as is shown in various real flight experiments performed with non-expert users.

There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth † to build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented.

Robotic vehicles that are capable of autonomously transitioning between various terrains and fluids have received notable attention in the past decade due to their potential to navigate previously unexplored and/or unpredictable environments. Specifically, aerial-aquatic mobility will enable robots to operate in cluttered aquatic environments and carry out a variety of sensing tasks. One of the principal challenges in the development of such vehicles is that the transition from water to flight is a power-intensive process. At a small scale, this is made more difficult by the limitations of electromechanical actuation and the unfavorable scaling of the physics involved. This paper investigates the use of solid reactants as a combustion gas source for consecutive aquatic jump-gliding sequences. We present an untethered robot that is capable of multiple launches from the water surface and of transitioning from jetting to a glide. The power required for aquatic jump-gliding is obtained by reacting calcium carbide powder with the available environmental water to produce combustible acetylene gas, allowing the robot to rapidly reach flight speed from water. The 160-gram robot could achieve a flight distance of 26 meters using 0.2 gram of calcium carbide. Here, the combustion process, jetting phase, and glide were modeled numerically and compared with experimental results. Combustion pressure and inertial measurements were collected on board during flight, and the vehicle trajectory and speed were analyzed using external tracking data. The proposed propulsion approach offers a promising solution for future high-power density aerial-aquatic propulsion in robotics.

Multi-UAV applications can be analyzed from the point of view of a complex system. Request-oriented deployment is a category of complex systems, in which the UAVs (the set of resources) are used to meet demands of the task requests (the set of needs). Task requests require aircrafts to attend to an occurrence location, perform a task on it and, finally, return and land on an available location. Literature proposes centralized, decentralized and hybrid strategies to coordinate such systems. This paper proposes a centralized framework, in which a single coordinator handles the task requests and assign UAVs to answer to these requests by means of the ground control station. The strategy aims at cost optimization, relying on mission partitioning and the analysis of multi-variables (such as wind bearing, battery state-of-charge, maneuvers and spatial position). The communication interface of the UAVs with the coordinator is formally defined by automata, which are generated on-the-fly based on configuration parameters provided by the human operator. Simulation results show that the framework is functional, safe and versatile in terms of custom cost optimization.

During the past years, camera-equipped Unmanned Aerial Vehicles (UAVs) have revolutionized aerial cinematography, allowing easy acquisition of impressive footage. In this context, autonomous functionalities based on machine learning and computer vision modules are gaining ground. During live coverage of outdoor events, an autonomous UAV may visually track and follow a specific target of interest, under a specific desired shot type, mainly adjusted by choosing appropriate focal length and UAV/camera trajectory relative to the target. However, the selected UAV/camera trajectory and the object tracker requirements (which impose limits on the maximum allowable focal length) affect the range of feasible shot types, thus constraining cinematography planning. Therefore, this paper explores the interplay between cinematography and computer vision in the area of autonomous UAV filming. UAV target-tracking trajectories are formalized and geometrically modeled, so as to analytically compute maximum allowable focal length per scenario, to avoid 2D visual tracker failure. Based on this constraint, formulas for estimating the appropriate focal length to achieve the desired shot type in each situation are extracted, so as to determine shot feasibility. Such rules can be embedded into practical UAV intelligent shooting systems, in order to enhance their robustness by facilitating on-the-fly adjustment of the cinematography plan.                    ACCESSIBLE AT: https://www.researchgate.net/publication/335011312_Shot_Type_Constraints_in_UAV_Cinematography_For_Autonomous_Target_Tracking

In this article, published in Journal of Agricultural and Environmental Ethics (Springer-Nature), innovation is connected to institutions. The empirical focus is on high-tech agriculture, which is a very dynamic area. While the literature on “responsible innovation” has opened our eyes regarding the importance of innovators to be ethically responsible, the present study illustrates the opposite logic: the importance of societal institutions, not least law makers and authorities, to be responsible towards innovators and adopters.

Agriculture is undergoing changes due to e.g. technology, competition and environmental concern. Among driving technologies are satellites, sensors, big data and precision machinery. In 2015, observers argued that the fourth agricultural revolution had been initiated. The article focuses on one part of this high-tech revolution: the origin, development, applications, and user value of “drones”, or unmanned aerial systems (UAS).

Institutional changes connected to the UAS innovation are analyzed, based on a Swedish case study. The methods included expert dialogues, autoetnography and literature studies. One important part of the project was the usage of conferences, during four years, for building empirical understanding.* The study has similarities with the model of knowledge production that Gibbons and others has called “Mode 2”.

The theoretical frame was composed by four perspectives: innovation, institutions, sustainability, and ethics. The departure of the discussion is an innovation model derived from an etymological study of the term innovation. This model is a four-field matrix based on two dimensions: originality and adoption. Also included in the model is the notion of barriers between the transformation of a phenomenon from one field to another in this matrix. Among the barriers for innovative concepts to transform into innovations, one can mention lack of marketing competence, trade fairs and potential users neglecting progress. Nut also institutions of various kinds can be barriers to innovations.

Regarding the institutional theory that we build on it has its roots in the Noble Prize winning theory formed by Douglass North and Robert Paul Thomas. Institutions mean “the rules of the game in society”. The essence of the theory is that institutions, especially the protection of property rights, can explain the progress of most countries of Western society, and thus are extremely important.

After theoretical discussions it is time for the empirical presentation. That part of the article starts with an historical description of the development of UAS. Then follows a discussion on different usages of UAS in agriculture around the world. Here is also included an in-depth study of a concrete farm: Wrams Gunnarstorp. At the farm Rudolf Tornerhjelm and his team uses UAS both for precision agriculture and other uses. Among precision agriculture uses are:

• Nutrients analysis
• Insect infestation analysis
• Fungus infestation analysis
• Snails attack mapping
• Moisture analysis to avoid soil compaction
• Drainage system analysis
• Harvest prediction

Among other uses at Wrams Gunnarstorp are:

• Forrest analysis after storms
• Analysis of wild animal (badgers etc.) interference
• Dialogue with insurance companies
• Providing arguments towards authorities (regarding biodiversity and cultivation)
• Planning of wetland and lake projects
• Inspection for house renovations
• Guiding the public including tourist visitors

A central part of the article is the discussion of future visions of UAS in agriculture. One of the visions is the following: The combination of drone-sensor data and other kinds of data, such as satellite, machine, weather and ground sensor data, will pave the way for bringing precision agriculture to higher levels. Cloud-based data fusion platforms like the one from the company CyStellar are already under way. Another vision is to use UAS to detect and rescue fawns or other wild animals hiding in agricultural fields. Thousands of animals are injured or killed every year by agricultural machines.

In summary, UAS can help farmers cut costs and produce higher quantity with better quality, and also has environmental (including animal care) benefits. However, this promising innovation was exposed to institutional forces and suddenly became subordinated the Act of Camera Surveillance. This study illuminates how legislative institutions sometimes can inhibit responsible innovation. Institutional changes are connected to ethics, and the study shows that different ethical perspectives can collide with each other.

Most of the ethical studies on UAS and other new technologies have focused on the (potential) negative dimensions, such as safety, integrity, security of data/information, dehumanization, and potential misuse. This study has focused on the other side of the coin and pointed towards the opportunities technologies can offer to address challenges, such as future food production and environmental sustainability. Above all, the study tries to connect institutional theory with innovation theory.

This article project was based on the Greenovation project (Grönovation) at Linköping University, partly funded by Vinnova and Region Östergötland.

* These conferences included Unmanned Flights in Agriculture and Forestry (Vreta Kloster, May 22, 2014), Agriculture Innovation Day (Ultuna, November 17, 2014), UAS Forum (Linköping, May 19–20, 2015), Conference on Unmanned Flying Systems – Opportunity or Threat? (Linköping, February 25, 2015), Aerospace Almedalen (Visby, July 2, 2015), Sweden Innovation Power, Agritechnica (Hannover, November 8–14, 2015), UAV Forum (Linköping, May 24–25 2016), Smart Farming (Vreta Kloster, September 29, 2016 and Torp, September 30, 2016), The Stenhammar Day (Flen, June 13, 2017), Drone Zone, Elmia Wood (Vaggeryd, June 9, 2017), Almedalen (Visby, July 3, 2017), UAS Forum (Linköping, October 3–4, 2017) and The Agriculture Day, Swedish Parliament (Stockholm, November 21, 2017).

The article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).