16,044 research outputs found
CARLA+: An Evolution of the CARLA Simulator for Complex Environment Using a Probabilistic Graphical Model
In an urban and uncontrolled environment, the presence of mixed traffic of autonomous vehicles, classical vehicles, vulnerable road users, e.g., pedestrians, and unprecedented dynamic events makes it challenging for the classical autonomous vehicle to navigate the traffic safely. Therefore, the realization of collaborative autonomous driving has the potential to improve road safety and traffic efficiency. However, an obvious challenge in this regard is how to define, model, and simulate the environment that captures the dynamics of a complex and urban environment. Therefore, in this research, we first define the dynamics of the envisioned environment, where we capture the dynamics relevant to the complex urban environment, specifically, highlighting the challenges that are unaddressed and are within the scope of collaborative autonomous driving. To this end, we model the dynamic urban environment leveraging a probabilistic graphical model (PGM). To develop the proposed solution, a realistic simulation environment is required. There are a number of simulators—CARLA (Car Learning to Act), one of the prominent ones, provides rich features and environment; however, it still fails on a few fronts, for example, it cannot fully capture the complexity of an urban environment. Moreover, the classical CARLA mainly relies on manual code and multiple conditional statements, and it provides no pre-defined way to do things automatically based on the dynamic simulation environment. Hence, there is an urgent need to extend the off-the-shelf CARLA with more sophisticated settings that can model the required dynamics. In this regard, we comprehensively design, develop, and implement an extension of a classical CARLA referred to as CARLA+ for the complex environment by integrating the PGM framework. It provides a unified framework to automate the behavior of different actors leveraging PGMs. Instead of manually catering to each condition, CARLA+ enables the user to automate the modeling of different dynamics of the environment. Therefore, to validate the proposed CARLA+, experiments with different settings are designed and conducted. The experimental results demonstrate that CARLA+ is flexible enough to allow users to model various scenarios, ranging from simple controlled models to complex models learned directly from real-world data. In the future, we plan to extend CARLA+ by allowing for more configurable parameters and more flexibility on the type of probabilistic networks and models one can choose. The open-source code of CARLA+ is made publicly available for researchers
Japanese Expert Teachers' Understanding of the Application of Rhythm in Judo: a New Pedagogy
Aim
The aim of this research is to understand the application of rhythm in judo through the experience of expert Japanese coaches.
Background
Scientists and experienced coaches agree rhythm is an important skill in people’s everyday life. There is currently no research that investigates the importance of rhythm in judo. People with a highly developed sense of rhythm, move properly, breathe properly, or begin and finish work at the right time. Where sport is concerned, motion and dance can play an important role not only in the improvement of performance, but also in the reduction, or even prevention of, injuries. Those who are naturally musically inclined (have a musical ear) may find they can improve their technique faster than others, and this is something that, by investigating the way expert coaches understand the application of rhythm in judo, this research seeks to understand.
As Lange, (1970) stated, factors of movement are ‘weight, space, time, and flow on the background of the general flux of movement in proportional arrangements’ (Bradley, 2008; Selioni, 2013; Youngerman, 1976), therefore, this research will investigate the interaction of body and mind. Dance training as well as judo are somatic experiences that have as their ultimate goal the attainment of a skilled body. With quality training an athlete gains an increased awareness of their body which leads to better control of movement and is very important for judo athletes. This training is found in Japanese kabuki dance (Hahn, 2007), the Greek syrtaki dance (Zografou & Pateraki, 2007), and in walking techniques used in the traditional and Olympic sports of Japanese judo and Greek wrestling.
Methods
Interpretative phenomenological analysis (IPA) was the most suitable data analysis approach for this study for a number of reasons, mainly because it was considered to most closely reflect the author's realist epistemological view. The idiographic approach and framework, particularly on IPA, was regarded as a useful framework in which the current topic could meaningfully be explored.
As this study is one of the first to explore this new thematic area, IPA was the preferred approach to address the goal of providing a detailed account of the expert’s experience. Therefore, semi-structured interviews were used as a data source. This is the most conventional form of data collection using IPA and most closely reflects the researcher-participant relationship. Semi-structured interviews provide considerable flexibility by allowing the researcher to be guided by the phenomena of interest to the participant.
In this study, purposive sampling was achieved using inclusion criteria pertaining to the research question.
Using the ranking system criteria based on the belt in combination with age employed by the International Judo Federation (IJF) and Kodokan Judo Institute, six expert coaches of forty years old and over with a minimum belt rank of 6th dan were selected as a sample.
Results
Both interviews and the codification process contributed to new findings regarding the application of rhythm to judo, and judo itself as a pedagogical tool.
The diagrammatic model can be considered a 'guideline' to the phenomena deemed most significant. The personal significance of rhythm in judo was evidenced by the frequency with which the interviewees naturally referred to it during the interviews. A number of interviewees said that it was important for rhythm to be second nature. Rhythm was also described as an integrated and representative
element in the context of training. This framework was seen as essential in providing the reader with a contextualised understanding of the phenomena considered most important for the current research. Interviewees reported various motives for employing training in rhythm such as faster technical development, better attack/defence, fitness, speed, skills acquisition, personal and spiritual growth, competition results.
Conclusions
This study offers first-hand accounts from professional coaches of a previously unknown phenomena, namely the use of rhythm in judo, and sheds insight on how judo experts understand rhythm in terms of training, competition, and personal growth. These findings suggest that outside of training, coaches play an important role in teaching, mentoring, and leading students. In conclusion, the research revealed four important points which form the basis of a new method of teaching judo: pedagogy, skills, rhythm and movement
Key technologies for safe and autonomous drones
Drones/UAVs are able to perform air operations that are very difficult to be performed by manned aircrafts. In addition, drones' usage brings significant economic savings and environmental benefits, while reducing risks to human life. In this paper, we present key technologies that enable development of drone systems. The technologies are identified based on the usages of drones (driven by COMP4DRONES project use cases). These technologies are grouped into four categories: U-space capabilities, system functions, payloads, and tools. Also, we present the contributions of the COMP4DRONES project to improve existing technologies. These contributions aim to ease drones’ customization, and enable their safe operation.This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 826610. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Austria, Belgium, Czech Republic, France, Italy, Latvia, Netherlands. The total project budget is 28,590,748.75 EUR (excluding ESIF partners), while the requested grant is 7,983,731.61 EUR to ECSEL JU, and 8,874,523.84 EUR of National and ESIF Funding. The project has been started on 1st October 2019
Meso-scale FDM material layout design strategies under manufacturability constraints and fracture conditions
In the manufacturability-driven design (MDD) perspective, manufacturability of the product or system is the most important of the design requirements. In addition to being able to ensure that complex designs (e.g., topology optimization) are manufacturable with a given process or process family, MDD also helps mechanical designers to take advantage of unique process-material effects generated during manufacturing. One of the most recognizable examples of this comes from the scanning-type family of additive manufacturing (AM) processes; the most notable and familiar member of this family is the fused deposition modeling (FDM) or fused filament fabrication (FFF) process. This process works by selectively depositing uniform, approximately isotropic beads or elements of molten thermoplastic material (typically structural engineering plastics) in a series of pre-specified traces to build each layer of the part. There are many interesting 2-D and 3-D mechanical design problems that can be explored by designing the layout of these elements. The resulting structured, hierarchical material (which is both manufacturable and customized layer-by-layer within the limits of the process and material) can be defined as a manufacturing process-driven structured material (MPDSM). This dissertation explores several practical methods for designing these element layouts for 2-D and 3-D meso-scale mechanical problems, focusing ultimately on design-for-fracture. Three different fracture conditions are explored: (1) cases where a crack must be prevented or stopped, (2) cases where the crack must be encouraged or accelerated, and (3) cases where cracks must grow in a simple pre-determined pattern. Several new design tools, including a mapping method for the FDM manufacturability constraints, three major literature reviews, the collection, organization, and analysis of several large (qualitative and quantitative) multi-scale datasets on the fracture behavior of FDM-processed materials, some new experimental equipment, and the refinement of a fast and simple g-code generator based on commercially-available software, were developed and refined to support the design of MPDSMs under fracture conditions. The refined design method and rules were experimentally validated using a series of case studies (involving both design and physical testing of the designs) at the end of the dissertation. Finally, a simple design guide for practicing engineers who are not experts in advanced solid mechanics nor process-tailored materials was developed from the results of this project.U of I OnlyAuthor's request
GelSight360: An Omnidirectional Camera-Based Tactile Sensor for Dexterous Robotic Manipulation
Camera-based tactile sensors have shown great promise in enhancing a robot's
ability to perform a variety of dexterous manipulation tasks. Advantages of
their use can be attributed to the high resolution tactile data and 3D depth
map reconstructions they can provide. Unfortunately, many of these tactile
sensors use either a flat sensing surface, sense on only one side of the
sensor's body, or have a bulky form-factor, making it difficult to integrate
the sensors with a variety of robotic grippers. Of the camera-based sensors
that do have all-around, curved sensing surfaces, many cannot provide 3D depth
maps; those that do often require optical designs specified to a particular
sensor geometry. In this work, we introduce GelSight360, a fingertip-like,
omnidirectional, camera-based tactile sensor capable of producing depth maps of
objects deforming the sensor's surface. In addition, we introduce a novel
cross-LED lighting scheme that can be implemented in different all-around
sensor geometries and sizes, allowing the sensor to easily be reconfigured and
attached to different grippers of varying DOFs. With this work, we enable
roboticists to quickly and easily customize high resolution tactile sensors to
fit their robotic system's needs
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The impact of innovative technologies in construction activities on concrete debris recycling in China : a system dynamics-based analysis
As construction activities become more intensive in developing countries, increasing improperly managed construction and demolition waste (CDW) brings serious environmental impacts. Recycling is a beneficial way to dispose of CDW that reduces environmental impact and brings economic benefits, especially for concrete. China is the country that generates the most CDW in the world, but its domestic recycling rate is much lower than that of developed countries. While the efficient technologies in developed regions have helped them to achieve a well-established recycling industry, whether these innovative technologies can be used to improve the concrete debris recycling targets in developing regions is unclear. This study examines whether innovations currently widely used in construction activities and materials can have a positive effect on the recycling of End-of-Life concrete materials in China. Results from modeling system dynamics imply that the introduction of innovative technologies in the recycling system of concrete debris can probably contribute to CO2 reduction (3.6% reduction) and economic benefits (2.6 times increase, but mainly from landfill charges and fines) from 2022 to 2030. Prefabrication and 3D printing significantly impact recycled concrete production and CDW recycling, and they are recommended as a priority for promotion. In contrast, carbonation is not suggested for application due to its minor role. Nevertheless, since the market share of innovative technologies and the basic CDW recycling rates are currently low in China, fluctuations in their usage are hardly to have a substantial positive impact. We suggest that financial support from the government is needed for upcycling by recyclers and technology providers to improve the base recycling rate in order for innovative technologies to make an effective contribution to the sustainable construction industry, creating a win–win situation for both the economy and the environment of the recycling system
A Design Science Research Approach to Smart and Collaborative Urban Supply Networks
Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness.
A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense.
Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence
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