Advancing automation and robotics technology for the Space Station Freedom and for the US economy

The progress made by levels 1, 2, and 3 of the Office of Space Station in developing and applying advanced automation and robotics technology is described. Emphasis is placed upon the Space Station Freedom Program responses to specific recommendations made in the Advanced Technology Advisory Committee (ATAC) progress report 10, the flight telerobotic servicer, and the Advanced Development Program. Assessments are presented for these and other areas as they apply to the advancement of automation and robotics technology for the Space Station Freedom

Department of Computer Science Activity 1998-2004

This report summarizes much of the research and teaching activity of the Department of Computer Science at Dartmouth College between late 1998 and late 2004. The material for this report was collected as part of the final report for NSF Institutional Infrastructure award EIA-9802068, which funded equipment and technical staff during that six-year period. This equipment and staff supported essentially all of the department\u27s research activity during that period

Model-Based Engineering of Collaborative Embedded Systems

This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years

Technology for the Future: In-Space Technology Experiments Program, part 2

The purpose of the Office of Aeronautics and Space Technology (OAST) In-Space Technology Experiments Program In-STEP 1988 Workshop was to identify and prioritize technologies that are critical for future national space programs and require validation in the space environment, and review current NASA (In-Reach) and industry/ university (Out-Reach) experiments. A prioritized list of the critical technology needs was developed for the following eight disciplines: structures; environmental effects; power systems and thermal management; fluid management and propulsion systems; automation and robotics; sensors and information systems; in-space systems; and humans in space. This is part two of two parts and contains the critical technology presentations for the eight theme elements and a summary listing of critical space technology needs for each theme

Artificial Intelligence as an Enabler of Quick and Effective Production Repurposing Manufactur-ing: An Exploratory Review and Future Research Propositions

The outbreak of Covid-19 created disruptions in manufacturing operations. One of the most serious negative impacts is the shortage of critical medical supplies. Manufacturing firms faced pressure from governments to use their manufacturing capacity to repurpose their production for meeting the critical demand for necessary products. For this purpose, recent advancements in technology and artificial intelligence (AI) could act as response solutions to conquer the threats linked with repurposing manufacturing (RM). The study’s purpose is to investigate the significance of AI in RM through a systematic literature review (SLR). This study gathered around 453 articles from the SCOPUS database in the selected research field. Structural Topic Modeling (STM) was utilized to generate emerging research themes from the selected documents on AI in RM. In addition, to study the research trends in the field of AI in RM, a bibliometric analysis was undertaken using the R-package. The findings of the study showed that there is a vast scope for research in this area as the yearly global production of articles in this field is limited. However, it is an evolving field and many research collaborations were identified. The study proposes a comprehensive research framework and propositions for future research development

Distributed reinforcement learning for self-reconfiguring modular robots

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 101-106).In this thesis, we study distributed reinforcement learning in the context of automating the design of decentralized control for groups of cooperating, coupled robots. Specifically, we develop a framework and algorithms for automatically generating distributed controllers for self-reconfiguring modular robots using reinforcement learning. The promise of self-reconfiguring modular robots is that of robustness, adaptability and versatility. Yet most state-of-the-art distributed controllers are laboriously handcrafted and task-specific, due to the inherent complexities of distributed, local-only control. In this thesis, we propose and develop a framework for using reinforcement learning for automatic generation of such controllers. The approach is profitable because reinforcement learning methods search for good behaviors during the lifetime of the learning agent, and are therefore applicable to online adaptation as well as automatic controller design. However, we must overcome the challenges due to the fundamental partial observability inherent in a distributed system such as a self reconfiguring modular robot. We use a family of policy search methods that we adapt to our distributed problem. The outcome of a local search is always influenced by the search space dimensionality, its starting point, and the amount and quality of available exploration through experience.(cont) We undertake a systematic study of the effects that certain robot and task parameters, such as the number of modules, presence of exploration constraints, availability of nearest-neighbor communications, and partial behavioral knowledge from previous experience, have on the speed and reliability of learning through policy search in self-reconfiguring modular robots. In the process, we develop novel algorithmic variations and compact search space representations for learning in our domain, which we test experimentally on a number of tasks. This thesis is an empirical study of reinforcement learning in a simulated lattice based self-reconfiguring modular robot domain. However, our results contribute to the broader understanding of automatic generation of group control and design of distributed reinforcement learning algorithms.by Paulina Varshavskaya.Ph.D

Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus

This is an open access book. It gathers the first volume of the proceedings of the 31st edition of the International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, held on June 19 – 23, 2022, in Detroit, Michigan, USA. Covering four thematic areas including Manufacturing Processes, Machine Tools, Manufacturing Systems, and Enabling Technologies, it reports on advanced manufacturing processes, and innovative materials for 3D printing, applications of machine learning, artificial intelligence and mixed reality in various production sectors, as well as important issues in human-robot collaboration, including methods for improving safety. Contributions also cover strategies to improve quality control, supply chain management and training in the manufacturing industry, and methods supporting circular supply chain and sustainable manufacturing. All in all, this book provides academicians, engineers and professionals with extensive information on both scientific and industrial advances in the converging fields of manufacturing, production, and automation

Factories of the Future

Engineering; Industrial engineering; Production engineerin

Robotic manipulators for single access surgery

This thesis explores the development of cooperative robotic manipulators for enhancing surgical precision and patient outcomes in single-access surgery and, specifically, Transanal Endoscopic Microsurgery (TEM). During these procedures, surgeons manipulate a heavy set of instruments via a mechanical clamp inserted in the patient’s body through a surgical port, resulting in imprecise movements, increased patient risks, and increased operating time. Therefore, an articulated robotic manipulator with passive joints is initially introduced, featuring built-in position and force sensors in each joint and electronic joint brakes for instant lock/release capability. The articulated manipulator concept is further improved with motorised joints, evolving into an active tool holder. The joints allow the incorporation of advanced robotic capabilities such as ultra-lightweight gravity compensation and hands-on kinematic reconfiguration, which can optimise the placement of the tool holder in the operating theatre. Due to the enhanced sensing capabilities, the application of the active robotic manipulator was further explored in conjunction with advanced image guidance approaches such as endomicroscopy. Recent advances in probe-based optical imaging such as confocal endomicroscopy is making inroads in clinical uses. However, the challenging manipulation of imaging probes hinders their practical adoption. Therefore, a combination of the fully cooperative robotic manipulator with a high-speed scanning endomicroscopy instrument is presented, simplifying the incorporation of optical biopsy techniques in routine surgical workflows. Finally, another embodiment of a cooperative robotic manipulator is presented as an input interface to control a highly-articulated robotic instrument for TEM. This master-slave interface alleviates the drawbacks of traditional master-slave devices, e.g., using clutching mechanics to compensate for the mismatch between slave and master workspaces, and the lack of intuitive manipulation feedback, e.g. joint limits, to the user. To address those drawbacks a joint-space robotic manipulator is proposed emulating the kinematic structure of the flexible robotic instrument under control.Open Acces