Computer Simulation of Human-Robot Collaboration in the Context of Industry Revolution 4.0

The essential role of robot simulation for industrial robots, in particular the collaborative robots is presented in this chapter. We begin by discussing the robot utilization in the industry which includes mobile robots, arm robots, and humanoid robots. The author emphasizes the application of collaborative robots in regard to industry revolution 4.0. Then, we present how the collaborative robot utilization in the industry can be achieved through computer simulation by means of virtual robots in simulated environments. The robot simulation presented here is based on open dynamic engine (ODE) using anyKode Marilou. The author surveys on the use of dynamic simulations in application of collaborative robots toward industry 4.0. Due to the challenging problems which related to humanoid robots for collaborative robots and behavior in human-robot collaboration, the use of robot simulation may open the opportunities in collaborative robotic research in the context of industry 4.0. As developing a real collaborative robot is still expensive and time-consuming, while accessing commercial collaborative robots is relatively limited; thus, the development of robot simulation can be an option for collaborative robotic research and education purposes

Virtual laboratories for education in science, technology, and engineering: A review

Within education, concepts such as distance learning, and open universities, are now becoming more widely used for teaching and learning. However, due to the nature of the subject domain, the teaching of Science, Technology, and Engineering are still relatively behind when using new technological approaches (particularly for online distance learning). The reason for this discrepancy lies in the fact that these fields often require laboratory exercises to provide effective skill acquisition and hands-on experience. Often it is difficult to make these laboratories accessible for online access. Either the real lab needs to be enabled for remote access or it needs to be replicated as a fully software-based virtual lab. We argue for the latter concept since it offers some advantages over remotely controlled real labs, which will be elaborated further in this paper. We are now seeing new emerging technologies that can overcome some of the potential difficulties in this area. These include: computer graphics, augmented reality, computational dynamics, and virtual worlds. This paper summarizes the state of the art in virtual laboratories and virtual worlds in the fields of science, technology, and engineering. The main research activity in these fields is discussed but special emphasis is put on the field of robotics due to the maturity of this area within the virtual-education community. This is not a coincidence; starting from its widely multidisciplinary character, robotics is a perfect example where all the other fields of engineering and physics can contribute. Thus, the use of virtual labs for other scientific and non-robotic engineering uses can be seen to share many of the same learning processes. This can include supporting the introduction of new concepts as part of learning about science and technology, and introducing more general engineering knowledge, through to supporting more constructive (and collaborative) education and training activities in a more complex engineering topic such as robotics. The objective of this paper is to outline this problem space in more detail and to create a valuable source of information that can help to define the starting position for future research

Simulation and Visualisation Software for an Elastic Aircraft for High Altitudes based on Game Engine Technology

The aim of this thesis work was to design and develop a simulation and visualization platform based on game engine technology, that could be applied to any robotic system and would provide tools for representing the robot, visualizing the environment around it in a high level of detail and also provide means of sampling this environment in order to enable external simulation of interactions between the robot and its surroundings. The main design goal is for the platform to be able to have external physics simulations (robot and robot-environment interactions) entirely separated from the game engine environment. To this end, Unreal Engine 4 (UE4) has been chosen and the platform was implemented as a modular UE4 project, by making use of engine-specific structures. Interfacing between these modules and external ones has been achieved by designing and implementing a middleware interface for the platform, therefore enabling access to the middlewares data transfer system. Finally, this software-in-the-loop chain created between the UE4 modules and the external modules with the middleware as a transfer point has been evaluated in terms of feasibility and functionality by conducting tests on the various modules and interfaces thereof. The outcome is a powerful, flexible and ready-to-use simulation and visualization platform that can be easily adapted to any robotic system and provides the necessary means to accurately sample a customizable, high-quality environment in the vicinity of the robot

Development of a robotic prototype system for the preparation and partition of radioactive products

The ionizing radiation is used in the nuclear medicine field during the execution of diagnosis exams. The continuous exposure of humans to the radiation may cause organs and tissues damage, being its severity dependent of the quantity of the radiation and the exposure time. The main objective of this work is to design a virtual environment to carry out the simulation of the several stages for the preparation of radioactive products based on the use of a robotic arm. In this work, the V-REP robotic simulation tool was used for the specification and development of the manipulation processes, without the need to consider the real manipulator, being timely and costly efficient. During this study, the preparation process of the dosages in the diagnostic exams was analyzed, being posteriorly translated into mechanical processes for a better perception. The materials and equipment needed were designed as virtual 3D models and posteriorly imported into the V-REP simulation platform in order to be distributed and programmed to achieve a closer approximation to reality.info:eu-repo/semantics/publishedVersio

ESMD Space Grant Faculty Project

No abstract availabl

Robot-Assisted Crowd Evacuation under Emergency Situations: A Survey

In the case of emergency situations, robotic systems can play a key role and save human lives in recovery and evacuation operations. To realize such a potential, we have to address many scientific and technical challenges encountered during robotic search and rescue missions. This paper reviews current state-of-the-art robotic technologies that have been deployed in the simulation of crowd evacuation, including both macroscopic and microscopic models used in simulating a crowd. Existing work on crowd simulation is analyzed and the robots used in crowd evacuation are introduced. Finally, the paper demonstrates how autonomous robots could be effectively deployed in disaster evacuation, as well as search and rescue missions

Locomoção de humanoides robusta e versátil baseada em controlo analítico e física residual

Humanoid robots are made to resemble humans but their locomotion abilities are far from ours in terms of agility and versatility. When humans walk on complex terrains or face external disturbances, they combine a set of strategies, unconsciously and efficiently, to regain stability. This thesis tackles the problem of developing a robust omnidirectional walking framework, which is able to generate versatile and agile locomotion on complex terrains. We designed and developed model-based and model-free walk engines and formulated the controllers using different approaches including classical and optimal control schemes and validated their performance through simulations and experiments. These frameworks have hierarchical structures that are composed of several layers. These layers are composed of several modules that are connected together to fade the complexity and increase the flexibility of the proposed frameworks. Additionally, they can be easily and quickly deployed on different platforms. Besides, we believe that using machine learning on top of analytical approaches is a key to open doors for humanoid robots to step out of laboratories. We proposed a tight coupling between analytical control and deep reinforcement learning. We augmented our analytical controller with reinforcement learning modules to learn how to regulate the walk engine parameters (planners and controllers) adaptively and generate residuals to adjust the robot’s target joint positions (residual physics). The effectiveness of the proposed frameworks was demonstrated and evaluated across a set of challenging simulation scenarios. The robot was able to generalize what it learned in one scenario, by displaying human-like locomotion skills in unforeseen circumstances, even in the presence of noise and external pushes.Os robôs humanoides são feitos para se parecerem com humanos, mas suas habilidades de locomoção estão longe das nossas em termos de agilidade e versatilidade. Quando os humanos caminham em terrenos complexos ou enfrentam distúrbios externos combinam diferentes estratégias, de forma inconsciente e eficiente, para recuperar a estabilidade. Esta tese aborda o problema de desenvolver um sistema robusto para andar de forma omnidirecional, capaz de gerar uma locomoção para robôs humanoides versátil e ágil em terrenos complexos. Projetámos e desenvolvemos motores de locomoção sem modelos e baseados em modelos. Formulámos os controladores usando diferentes abordagens, incluindo esquemas de controlo clássicos e ideais, e validámos o seu desempenho por meio de simulações e experiências reais. Estes frameworks têm estruturas hierárquicas compostas por várias camadas. Essas camadas são compostas por vários módulos que são conectados entre si para diminuir a complexidade e aumentar a flexibilidade dos frameworks propostos. Adicionalmente, o sistema pode ser implementado em diferentes plataformas de forma fácil. Acreditamos que o uso de aprendizagem automática sobre abordagens analíticas é a chave para abrir as portas para robôs humanoides saírem dos laboratórios. Propusemos um forte acoplamento entre controlo analítico e aprendizagem profunda por reforço. Expandimos o nosso controlador analítico com módulos de aprendizagem por reforço para aprender como regular os parâmetros do motor de caminhada (planeadores e controladores) de forma adaptativa e gerar resíduos para ajustar as posições das juntas alvo do robô (física residual). A eficácia das estruturas propostas foi demonstrada e avaliada em um conjunto de cenários de simulação desafiadores. O robô foi capaz de generalizar o que aprendeu em um cenário, exibindo habilidades de locomoção humanas em circunstâncias imprevistas, mesmo na presença de ruído e impulsos externos.Programa Doutoral em Informátic