Design & Development of a Robotic System Using LEGO Mindstorm

This research presents a design and development of robotic system based on LEGO Mindstorm kit. The system is capable in operating an off-line programming method, starting from its programming sequences until robotic implementation of the program. During early stages, the research is emphasis more towards designing a robotic system using RoboLab software and C++ programming language. A robotic hardware system has been developed using LEGO Mindstorm kit. The robotic model acts as a prototype or test-bed for programming execution. The model involves motorize movement, sensors detection and machine vision to be manipulated by the programmers inside their programs. Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. For this research, several set of robots by using Lego has been developed and it uses LeJos and C programming techniques as a platform. A Java-based robot development tool has been set up as alternative programming methods incorporating LeJos and the controller. A prototype of a mobile robot based on Lego successfully implemented by using PIC and can be controlled through voice recognition

Assessment of Human Performance in Industry 5.0 Research Via Eye-Tracking and Cognitive Biases

Manufacturing assembly is combining previously made components or subassemblies into a final finished product. The assembly process can be manual, hybrid, or fully automated. Human operators who are involved in assembly use their judgment to perform the process. They collaborate with the other work agents such as assembly machines, robots, smart technologies, and computer interfaces. The recent Industrial revolution, Industry 5.0, exploits human expertise in collaboration with efficient and accurate machines. Manufacturing facilities that feature Industry 5.0 work settings require higher expectations, higher accuracy, sustainability solutions, mass customization of products, more human involvement, and digital technologies in smart workstations. Given these features, the cognitive load exerted on human workers in this environment is continuously increasing, leading to the use of cognitive heuristics. Cognitive biases are getting more attention in the cognitive ergonomics field, to help understand the operational behavior of workers. Manufacturing facilities can integrate cognitive assistance systems to work in parallel with physical and sensorial assistance systems. Cognitive assistance systems help toward better work conditions for workers and better overall system performance. This research explores the impact of human thinking style and using a cognitive assistance system on workers\u27 cognitive load, bias-related human performance, and user satisfaction. This research presents the design and experimental implementation of a research framework based on a well-established three-layer model for implementing Industry 5.0 in manufacturing. The research framework was designed to apply the dual-system theory and cognitive assistance in Assembly 5.0. Two experiments are presented to show the effectiveness of the proposed research framework. A cognitive assistance system was designed and compared to a benchmark system from LEGO ® Company. Subjective and objective measures were used to assess the thinking style, cognitive load, bias-related human performance, and user satisfaction in Assembly 5.0. As Industry 5.0 requires higher expectations, higher accuracy, smart workstations, and higher complexity, cognitive assistance systems can reduce the cognitive load and maintain the work efficiency and user satisfaction. Therefore, this work is important to industry to expand the use of cognitive ergonomic tools and employ them for A5.0 workers\u27 benefits

Assessment of Human Performance in Industry 5.0 Research Via Eye-Tracking and Cognitive Biases

Manufacturing assembly is combining previously made components or subassemblies into a final finished product. The assembly process can be manual, hybrid, or fully automated. Human operators who are involved in assembly use their judgment to perform the process. They collaborate with the other work agents such as assembly machines, robots, smart technologies, and computer interfaces. The recent Industrial revolution, Industry 5.0, exploits human expertise in collaboration with efficient and accurate machines. Manufacturing facilities that feature Industry 5.0 work settings require higher expectations, higher accuracy, sustainability solutions, mass customization of products, more human involvement, and digital technologies in smart workstations. Given these features, the cognitive load exerted on human workers in this environment is continuously increasing, leading to the use of cognitive heuristics. Cognitive biases are getting more attention in the cognitive ergonomics field, to help understand the operational behavior of workers. Manufacturing facilities can integrate cognitive assistance systems to work in parallel with physical and sensorial assistance systems. Cognitive assistance systems help toward better work conditions for workers and better overall system performance. This research explores the impact of human thinking style and using a cognitive assistance system on workers\u27 cognitive load, bias-related human performance, and user satisfaction. This research presents the design and experimental implementation of a research framework based on a well-established three-layer model for implementing Industry 5.0 in manufacturing. The research framework was designed to apply the dual-system theory and cognitive assistance in Assembly 5.0. Two experiments are presented to show the effectiveness of the proposed research framework. A cognitive assistance system was designed and compared to a benchmark system from LEGO ® Company. Subjective and objective measures were used to assess the thinking style, cognitive load, bias-related human performance, and user satisfaction in Assembly 5.0. As Industry 5.0 requires higher expectations, higher accuracy, smart workstations, and higher complexity, cognitive assistance systems can reduce the cognitive load and maintain the work efficiency and user satisfaction. Therefore, this work is important to industry to expand the use of cognitive ergonomic tools and employ them for A5.0 workers\u27 benefits

Serious Play Approaches for Creating, Sharing, and Mobilizing Tacit Knowledge in Cross-disciplinary Settings

abstract: Serious play—the notion of bringing the benefits of play to bear on work-related tasks—is receiving more attention as a remedy to many challenges of the modern knowledge economy. Exploring and defining the role of serious play approaches to facilitate collaborative problem-solving and value creation, this dissertation consists of four related research papers. The first research paper (RP1) reconciles three different conceptualizations of knowledge into a new theory of knowledge. This pluralistic definition allows knowledge to change character across the span of the value creation process. The paper further introduces a model called the Wheel of Knowledge (WoK) for mobilizing knowledge throughout the different knowledge conversions of the value creation process. The second research paper (RP2) advocates that serious play can scaffold and accelerate these knowledge conversion processes, it disaggregates existing serious play approaches, and starts to operationalize the WoK by using it to match different types of serious play approaches to different types of knowledge conversion challenges. The third research paper (RP3) validates the WoK by sorting the serious play literature according to how it applies to the different knowledge conversion processes. The paper provides a framework for ascertaining the applicability of serious play methods to specific knowledge conversion challenges and identifies under-explored research areas of the serious play field. The fourth research paper (RP4) tests the recommendations of RP3 by applying the LEGO® Serious Play® (LSP) method to a knowledge conversion challenge focused on tacit knowledge sharing. It reports on a mixed-methods, multi-session case study in which LSP was used to facilitate cross-disciplinary dialogue and deliberation about a wicked problem. Results show that LSP is particularly useful in the beginning of a value creation process and that it facilitates socialization and tacit knowledge sharing. Taken together the papers demonstrate the necessity, potential, and application of serious play as a catalyst for the knowledge conversion processes presented in the WoK. It is now clear that different serious play approaches are suitable as respectively: an accelerator for trust-building and collective creativity, as a conduit for iterative innovation, and as a way of making rote tasks more engaging.Dissertation/ThesisDoctoral Dissertation Design 201

Robomaths: Robotics to Learn Matematics in a Architecture Degree

The abstract part of mathematics is a difficult matter included in many subjects in university degrees. Specifically, in architecture degrees students lack interest in this topic if they don’t experience its immediate application. In addition, technological skills are required at every educational level and the students of these degrees are usually more interested in art than in technology. With the aim of encouraging architecture students' interest in mathematics and technology, a methodology is presented here that includes the use of robotics in maths lectures. The key idea is to make the abstract part of mathematics understandable by means of robots

A Systemic comparison of different chimeric antigen receptor (car) designs for retargeting of NK-92 cells against tumor antigens

Cancer immunotherapies focus on the power of the immune system to attack tumor cells. Recently, Chimeric Antigen Receptors expressing T cells (CAR-T cells) have received clinical approval for antigen-specific adoptive immunotherapy against CD19 in B cell malignancies. CAR vector designs have dramatically developed since their initial discovery and now include first-generation CARs (CD3ζ-based CAR), second-generation CARs with additional costimulatory domains such as CD28 or CD137 and third generation CARs (CD3ζ with two costimulatory domains) and recently fourth generation CAR with a transgene for cytokine stimulation. Natural Killer (NK) cells have ability recognize the tumor cells by their native receptors and have grown to be promising candidates for adoptive immunotherapy of cancer. CAR expression in NK cells is also clinically tested and carries the potential to translate into clinical application but the majority of literature on CAR vector design relies on observations from T cells. This thesis aims to use NK-92 cells for evaluation of different designs in order to optimize a CAR vector that could be efficiently used to retarget NK cells against tumor antigens. CAR transgenes comprising identical antigen binding domains that target CD19, combined with different intracellular signaling domains (CD3ζ , CD28 and CD137) are transferred to NK-92 cells via the use of lentiviral vectors. Cytotoxic activity and antigen-specificity of CAR-NK-92 cells are evaluated against the CD19- classical NK cell target K562 cell line and the CD19+ cell line Daudi and Namalwa by analysis of degranulation and cytokine secretion. Our results provide valuable data for optimal CAR vector design in NK cell