Philosophiae Doctor - PhD / E-government should be at the heart of service delivery in developing countries if the life of citizens, especially the socially and economically marginalised, is to be improved. Often in developing contexts, citizens have been treated as recipients of such interventions, in a top-down approach from central governments, resulting in the non-use of such interventions. A situation of non-use of e-services results in wastage of the public fiscus. The extant literature points to a number of underlying causes of the problem. One such problem is the “Design-Reality Gap."

As progress pushes the boundaries of both the performance of new hardware components and the computational capacity of modern computers, the requirements on the performance of robotic systems are becoming more and more demanding. The objective of this thesis is to demonstrate that concurrent design (Co-Design) is the approach to follow to design hardware and control for such high-performance robots. In particular, this work proposes a co-design framework and an algorithm to tackle two main issues: i) how to use Co-Design to benchmark different robotic systems, and ii) how to effectively warm-start the trajectory optimization (TO) problem underlying the co-design problem aiming at global optimality. The first contribution of this thesis is a co-design framework for the energy efficiency analysis of a redundant actuation architecture combining Quasi-Direct Drive (QDD) motors and Series Elastic Actuators (SEAs). The energy consumption of the redundant actuation system is compared to that of Geared Motors (GMs) and SEAs alone. This comparison is made considering two robotic systems performing different tasks. The results show that, using the redundant actuation, one can save up to 99% of energy with respect to SEA for sinusoidal movements. This efficiency is achieved by exploiting the coupled dynamics of the two actuators, resulting in a latching-like control strategy. The analysis also shows that these large energy savings are not straightforwardly extendable to non-sinusoidal movements, but smaller savings (e.g., 7%) are nonetheless possible. The results highlight that the combination of complex hardware morphologies and advanced numerical Co-Design can lead to peak hardware performance that would be unattainable by human intuition alone. Moreover, it is also shown how to leverage Stochastic Programming (SP) to extend a similar co-design framework to design robots that are robust to disturbances by combining TO, morphology and feedback control optimization. The second contribution is a first step towards addressing the non-convexity of complex co-design optimization problems. To this aim, an algorithm for the optimal control of dynamical systems is designed that combines TO and Reinforcement Learning (RL) in a single framework. This algorithm tackles the two main limitations of TO and RL when applied to continuous-space non-linear systems to minimize a non-convex cost function: TO can get stuck in poor local minima when the search is not initialized close to a “good” minimum, whereas the RL training process may be excessively long and strongly dependent on the exploration strategy. Thus, the proposed algorithm learns a “good” control policy via TO-guided RL policy search. Using this policy to compute an initial guess for TO, makes the trajectory optimization process less prone to converge to poor local optima. The method is validated on several reaching problems featuring non-convex obstacle avoidance with different dynamical systems. The results show the great capabilities of the algorithm in escaping local minima, while being more computationally efficient than the state-of-the-art RL algorithms Deep Deterministic Policy Gradient and Proximal Policy Optimization. The current algorithm deals only with the control side of a co-design problem, but future work will extend it to include also hardware optimization. All things considered, this work advanced the state of the art on Co-Design, providing a framework and an algorithm to design both hardware and control for high-performance robots and aiming to the global optimality.

Yes / Background: Experience-based co-design (EBCD) brings patients and staff together to co-design services. It is normally conducted in one organization which initiates and implements the process. We used the traditional EBCD method with a number of adaptations as part of a larger research study in the British National Health Service.Methods: The primary aim was to assess the feasibility and acceptability of conduct-ing research-initiated EBCD, to enhance intervention development prior to testing. As well as embedding the method in a research study, there were 3 further key adap-tations: (a) working across primary and secondary care sectors, (b) working on multi-ple sites and (c) incorporating theory-informed analysis.Results: We recruited four sites (covering both primary and secondary care) and, on each site, conducted the initial traditional EBCD meetings, with separate staff and patient groups—followed by a single joint patient-staff event, where four priority areas for co-design were agreed. This event was driven by theory-informed analysis, as well as the traditional trigger film of patient experiences. Each site worked on one priority area, and the four co-design groups met over 2-3 months to design prototype tools. A second joint event was held (not usually undertaken in single-site EBCD) where they shared and compared outputs. The research team combined elements of these outputs to create an intervention, now being tested in a cluster randomized controlled trial.Conclusions: EBCD can be successfully adapted for use across an entire patient pathway with multiple organizations and as part of a research process to identify an intervention for subsequent testing in a randomized trial. Our pragmatic approach used the patient experience to identify areas for improvement and co-designed an intervention which directly reflected patient priorities. / National Institute for Health Research programme ‘Improving the safety and continuity of medicines management at care transitions (ISCOMAT)’ RP‐PG‐0514‐2009.

Yes / Optimising the use of patient data has the potential to produce a transformational change in healthcare planning, treatment, condition prevention and understanding disease progression. Establishing how people's trust could be secured and a social licence to share data could be achieved is of paramount importance. The study took place across Yorkshire and the Humber, in the North of the England, using a sequential mixed methods approach comprising focus groups, surveys and co-design groups. Twelve focus groups explored people's response to how their health and social care data is, could, and should be used. A survey examined who should be able to see health and care records, acceptable uses of anonymous health and care records, and trust in different organisations. Case study cards addressed willingness for data to be used for different purposes. Co-creation workshops produced a set of guidelines for how data should be used. Focus group participants (n = 80) supported sharing health and care data for direct care and were surprised that this is not already happening. They discussed concerns about the currency and accuracy of their records and possible stigma associated with certain diagnoses, such as mental health conditions. They were less supportive of social care access to their records. They discussed three main concerns about their data being used for research or service planning: being identified; security limitations; and the potential rationing of care on the basis of information in their record such as their lifestyle choices. Survey respondents (n = 1031) agreed that their GP (98 %) and hospital doctors and nurses (93 %) should be able to see their health and care records. There was more limited support for pharmacists (37 %), care staff (36 %), social workers (24 %) and researchers (24 %). Respondents thought their health and social care records should be used to help plan services (88 %), to help people stay healthy (67 %), to help find cures for diseases (67 %), for research for the public good (58 %), but only 16 % for commercial research. Co-creation groups developed a set of principles for a social licence for data sharing based around good governance, effective processes, the type of organisation, and the ability to opt in and out. People support their data being shared for a range of purposes and co-designed a set of principles that would secure their trust and consent to data sharing. / This work was supported by Humber Teaching NHS Foundation Trust and the National Institute for Health Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre (NIHR Yorkshire and Humber PSTRC).

Engineered products can impact the day-to-day life of their users and other stakeholders. These impacts are often referred to as the product's social impacts. Products have been known to impact the people who use them, design them, manufacture them, distribute them, and the communities where they exist. Currently, there are few methods that can help an engineer identify, quantify, predict, or improve a product's social impact. Some companies and organizations have tried to identify their impacts and, for example, set goals for achieving more sustainable business practices. However, engineers, in large part, do not have methods that can help improve the sustainability and social impacts of their products. Without new methods to help engineers make better product decisions, products will continue to have unanticipated negative impacts and will likely not reach their true social impact potential. Engineers working in the field of Engineering for Global Development (EGD) are especially in need of methods that can help improve the social impacts of their products. One of the purposes of creating products in EGD is to help solve problems that lead to improved quality of life for people and communities in developing countries. The research in this dissertation presents new methods developed to help engineers understand, predict, and improve the social impact of their products. Chapter 2 introduces the Product Impact Metric, a simple metric engineers can use to quantify their products impact on improving the quality of life of impoverished individuals in developing countries. Chapter 3 introduces a method that engineers can use to create product-specific social impact metrics and models. These models are used to predict the social impacts of an expanded US-Mexico border wall on immigrants, border patrol officers, and local communities. Chapter 4 shows a method that allows engineers to create social impact models for individuals within a population. Using data available through online databanks and census reports, the author predicts the social impact of a new semi-automated cassava peeler on farmers in the Brazilian Amazon. In Chapter 5, the author presents a method for engineers to optimize a product according to its social impact on multiple stakeholders. Inspired by existing literature on multi-stakeholder decision making, eight different optimization problem formulations are presented and demonstrated in an example with the cassava peeler. Chapter 6 presents the author's experience in co-designing a semi-automated cassava with the Itacoatiara Rural Farming Cooperative. The peeler was designed and built by the author and is used as the example in Chapters 4 and 5. Finally, Chapter 7 shows the conclusions the author has in completing this research. Comments are made as to the difficulties encountered in this research (specifically data quality and validation), and the author makes suggestions of possible future work.

Due to various societal changes such as globalization, urbanization and connectivity, new lifestyles, such as that of urban nomads, are becoming more common and relevant. Therefore, this study observes and analyzes this target group from a critical and multidisciplinary perspective. Urban nomads can be defined as a collective group of people who live and work in urban areas. They do not reside permanently in one place but move frequently within urban locations. Minimalism as part of low-consumption lifestyles and the concept of mobility, which form the core of the urban nomads‘ mindset, are examined in detail.The focus of the research is the relationship of urban nomads to material possessions and their meaning. Based on this, the thesis aims to generate criteria and requirements for a product design from the perspective of design, which meets the needs of urban nomads and simplifies their everyday life. Through a people-centered approach and the collaborative application of different methods, the urban nomads are placed in the focus of the innovation process and are actively involved in the process.The thesis results in the development of a transportable and multifunctional lamp (Mobilamp), which is realized in the form of a prototype based on the generated criteria from the research. The product design is considered as an example and analyzes in which way needs can be satisfied and through which usage situations the daily life of urban nomads can be facilitated. The aspect of sustainability in the consumption behavior of the target group is also critically analyzed and evaluated through the product.

Appealing participants' engagement drives collaborative systems to enhance it through system's use or through system's design. However, engaging participants in collaborative systems to create digital resources is not trivial to achieve as the majority of contributions are provided by a very small percentage of engaged participants. In the literature, different approaches, such as human-in-the-loop and co-design, investigate engagement in these lines. This thesis aims to study how reflexivity can help designers to investigate participants' engagement in co-design of collaborative systems. Based on a qualitative approach, the thesis is positioned in the field of Human Computer Interaction and grounded on two studies. The retrospective analysis of the two studies was guided through a framework composed of three phases. In the first phase, supported by the literature review, several qualitative methods were investigated to identify the communities to be involved in the research; in the second phase, different co-design sessions were conducted with participants; and in the third phase, participants evaluated the solutions co-designed. The two studies followed different but intertwined approaches. Study 1 followed a user-centric approach and supported the identification and consolidation of a set of factors that hindered or facilitated engagement. The factors were articulated as barriers, drivers, and workarounds, and were validated in Study 2, which followed a participative approach. These factors constitute the first contribution of this thesis. Moreover, the literature review and the empirical data supported the identification of three dimensions to facilitate the adoption of a reflexive approach in co-design. These dimensions correspond to the second contribution of this thesis. Finally, the set of barriers, drivers, and workarounds was merged with the dimensions to propose a framework to investigate engagement in co-design of collaborative systems, constituting the third contribution of this thesis.

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This thesis project explores the research question of “How can vulnerable groups be encouraged to contribute with genuine personal content to a shared entity (the archive) in a scalable way?”. The project applies co-design practices in order to identify qualities that a system for collaborative self-archiving should incorporate in order to engage vulnerable groups to contribute to the archive, more specifically exploring what would motivate the refugees in Sweden to contribute to the Swedish archive. Several workshops have been run together with the target group, preceded by sensitizing exercises and interviews and supported by additional field research of the other stakeholders for the subject explored - the professional archivists and the Swedish citizens.

Ocean wave energy has the potential to play a crucial role in the shift to renewable energy. In order to improve wave energy conversion techniques, a recognition of the sub-optimal nature of traditional sequential design processes due to the interconnectedness of subsystems such as the geometry, power take-off, and controls is necessary. A codesign optimization in this paper seeks to include effects of all subsystems within one optimization loop in order to reach a fully optimal design for an oscillating-surge wave energy converter. A width and height sweep serves as a brute force geometry optimization while optimizing the power take-off components and controls using a pseudo-spectral method for each geometry. An investigation of electrical power and mechanical power maximization also outlines the contrasting nature of the two objectives to illustrate electrical power maximization's importance for identifying optimality. The codesign optimization leads to an optimal design with a width of 12 m and a height of 10 m. The power take-off and controls systems are also examined more in depth to identify important areas for increased focus during detailed design. Ultimately, the codesign optimization leads to a 61.4% increase in the objective function over the optimal design from a sequential design process while also requiring about half the power take-off torque. / Master of Science / Ocean wave energy has the potential to play a crucial role in the shift to renewable energy sources. The Earth's vast oceans have immense energy potentials throughout the world, which often follow the seasonal trends of electricity demand in temperate climates. Wave energy harvesting is a technology which has been studied significantly, but has not yet experienced commercial success, partially due to the lack of convergence on a type of wave energy converter. In order to improve wave energy conversion techniques and support the convergence on a particular type, a recognition of the sub-optimal nature of traditional sequential design processes due to the interconnectedness of subsystems is necessary. A codesign optimization in this paper seeks to include effects of all subsystems within one optimization loop in order to reach a fully optimal design for an oscillating-surge wave energy converter. A width and height sweep serves as a brute force geometry optimization while optimizing the power take-off and control components for each geometry. The codesign optimization leads to an optimal design with a width of 12 m and a height of 10 m. Ultimately, the codesign optimization leads to a 62% increase in performance over the result from a sequential design process.