. "Automation And Robotics"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Space software"@en . . "7.5" . "Requirements Definition, Software Architectures, Methods, Tools, Management, Verification and Validation, Transfer, Operations and Maintenance, and Quality" . . "Hybrid"@en . "FALSE" . . "Space automation and robotics"@en . . "7.5" . "Systems, Components, Technologies" . . "Hybrid"@en . "FALSE" . . "Parametric modelling of mechanical objects"@en . . "3" . "The course provides an in-depth understanding of the capabilities of parametric modelling software using Autodesk Inventor Professional. The design tasks of typical elements and mechanisms of aviation technics provide an in-depth understanding of the development and editing of parametric sketches, the complex assembly of complex kinematics mechanisms, their development and the study of the dynamics and strength of their elements.\n\nOutcome:\nKnows the structure, principles of operation, kinematics and dynamics of important mechanisms and components of aviation equipment. - Practical tasks. Control work. Exam.\r\nAble to develop the details and assembly of the mechanism based on the calculation results. - Practical tasks. Control work. Exam.\r\nAble to calculate the strength of the mechanism elements by the finite element method. - Practical tasks. Control work. Exam.\r\nAble to perform computer simulation of mechanism dynamics. - Practical tasks. Control work. Exam.\r\nAble to apply the capabilities of modern software products to solve specific object modeling tasks - Practical tasks. Exam." . . "Presential"@en . "TRUE" . . "Advanced robotics"@en . . "5" . "Aims:\r\n\r\nThe aims of the course are to:\r\n\r\nLearn advanced topics of robotics (underactuated robotics, robot learning, soft robotics, human robot interactions, and distributed robotics)\r\nFundamentals (theories and methodologies) of advanced robotics researches\r\nPractical implementation of advanced robotics technologies\n\nOutcome:\nAs specific objectives, by the end of the course students should be able to:\r\n\r\nExtend the knowledge of introductory robotics to more advanced ones to carry out research\r\nLearn research techniques and skills for robotics projects\r\nWork effectively with collaborators in robotics projects\r\nDeliver professional presentations and communication of robotics projects\r\n* This module is shared with 4th Year undergraduates from the Department of Engineering." . . "Presential"@en . "TRUE" . . "Introduction to robotics"@en . . "5" . "Aims\r\n\r\nThe aims of the course are to:\r\n\r\nIntroduce fundamentals of robotics\r\nLearning technologies and techniques to design, assemble, and control robots\r\nHands-on exercises on robot development through projects\r\nPresentation of research and development\n\nOutcome:\nAs specific objectives, by the end of the course students should be able to:\r\n\r\nLearning different design strategies and architectures of robots\r\nDesign methods of automated complex systems\r\nDevelopment of simulated complex robots\r\nModel-based analysis robot performance\r\n* This module is shared with 4th Year undergraduates from the Department of Engineering." . . "Presential"@en . "FALSE" . . "Introduction to space robotics"@en . . "5" . "This course will cover the following topics: · What is robot: history and applications · Basics of feedback control · Design consideration in space robots · Orbital robotics o History of robotic manipulators for orbital missions o Kinematics, dynamics and control of free-flying robots o Vibration dynamics and suppression control o Target capture and impact dynamics o Hardware test bed principles for the motion in micro-gravity · Lunar/planetary robotics o History of lunar/planetary robots o Mobility system design for surface locomotion o Wheel-soil traction mechanics o Sensing and navigation o Localization and mapping · Teleoperation and autonomy o Communication bandwidth and latency in teleoperation o Shared autonomy\n\nOutcome:\r\nHaving taken this course students will be able to · Answer to “what”, “why” and “how” questions about robots and their application to space missions. · Outline the basics of robot control and the challenges of space robotics. · Describe the principle core technologies for both Earth orbital robotics and lunar/planetary robotics." . . "Presential"@en . "TRUE" . . "Robotic technologies for space"@en . . "5" . "The student has knowledge of the application of robotic technologies in aerospace - from the construction of orbiting satellites and landing modules designed to explore other space bodies to assistance systems for manned cosmonautics. He/she understands the principles of sensors and actuators for use in robotic applications. He/she knows the basic mechanical structures of robotic arms and mobile chassis, as well as various ways of their control. He/she can design a suitable type of interface between the operator and the controlled robotic device.\n\nThe student will gain knowledge:\n- design of robotic manipulators\n- design of mobile robots\n- various aspects of human-robot interaction\n- robotic applications in aerospace\n\nThe student will gain skills:\n- selection of a suitable type of kinematic structure\n- selection of a suitable type of drive and sensor system\n- selection of a suitable type of robot control\n\nThe student acquires competencies:\n- select a suitable type of robot for specific applications in aerospace\n- design its kinematic structure, propulsion and sensor system\n- participate in the design of various types of robotic applications\n- participate in research in the field of aerospace robotics Course Contents:\n1. Robotics - Definition of subject, related scientific and technical disciplines, historical milestones of robotics development in connection with distance exploration of Earth and other cosmic bodies.\n2. Robot and its subsystems, autonomous and remote-controlled systems, robot classification according to various criteria\n3. Mobile robots - design principles of robots moving on a solid surface, on and below the (water) surface, respectively, in the gaseous atmosphere and in the cosmic space. Position and orientation control. Methods of landing on cosmic bodies of different types.\n4. Robotic manipulators and other mechanical constructions for use on mobile platforms and piloted cosmonauts. Description of basic kinematic structures. Exoskeleton.\n5. Driving systems for use in robotics, motors and transmission mechanisms - basic description and properties\n6. Sensory systems for use in robotics - basic principles and properties. Sensors of internal variables, sensors of localization systems. Sensors for remote and in situ exploration of physical properties of cosmic bodies.\n7. Power sources for mobile robots, energy management, internal temperature stabilization, protecting systems against adverse environmental influences.\n8. Human-robot interaction - basic ways of controlling and programming robots. Ways to communicate with robots. Visual and haptic feedback. Enhanced and virtual reality.\n9. Current applications of robots and robotic technologies in remote Earth exploration and exploration of other cosmic bodies. Robotics in piloted cosmonautics.\n10. Trends in the development of robotics with a focus on remote Earth exploration and other cosmic bodies. Service robotics. Sample gathering and transport to the Earth. Mining of raw materials on other cosmic bodies." . . "Presential"@en . "TRUE" . . "Robotics I"@en . . "6" . "Learning outcomes\nAfter completing this course, the student will:\n* have used programming languages;\n* have used a robot platform based on the Raspberry PI;\n* knows what a robot is;\n* know how a robotics system is structured;\n* know the most used sensors and actuators;\n* know the most important movement mechanisms in robotics;\n* know some options to position a robot;\n* know about some communication solutions;\n* be able to gather and analyse data using a robot;\n* be able to use gathered knowledge in a robotics project.\nBrief description of content\nIntroduction into robotics systems using a Raspberry Pi and Arduino in combination with GoPiGo platform. The main programming language used is Python but some Arduino C++ is also covered." . . "Presential"@en . "TRUE" . . "Project in competitive robotics"@en . . "6" . "Learning outcomes\nFinish a hardware project in a group where time is of the essence. Quickly aqcuire missing knowledge.\nBrief description of content\nStudents will be asigned into groups of 3 to 4 people. Each team will build a robot that complies with the rules of Robotex (http://www.robotex.ee).\nBuilding a robot consists of:\nbuilding a chassis\ninstalling of sensors\nthe interconnecting of sensors and actuators with microcontrollers\nprogramming of microcontrollers\ntesting of finished solution\nAll students with some knowledge in mechanics, low level programming, high level programming or project and team management are welcome.\nEach team will be composed in such a way that the skills of members will complement eachother.\nTo attend the course, you will need to attend the kickoff camp. More information will be given in the first lecture." . . "Presential"@en . "TRUE" . . "Soft robotics"@en . . "3" . "Learning outcomes\nAfter completing the course, the student can:\n1. define the application domain for soft robotics;\n2. explain the relation of soft robotics to robotics, chemistry, and biology;\n3. explain the defining concepts in soft robotics using relevant examples;\n4. list, explain and compare the prevalent technologies in modern soft robotics;\n5. critically read and elaborate on scientific texts on soft robotics.\n6. list the particular advantages of soft robotics, using relevant examples,\n7. explain the benefits of bioinspired design in relevant contexts;\n8. Identify elements in nature that are relevant for soft robotics and formulate their core principles in terms of robotics technology;\n9. apply the principles of soft (bioinspired) robotics by suggesting a new design in a practical setting;\nBrief description of content\nThe course gives an introduction to soft robotics discipline, its relevant technologies, and its relation to nature in the context of bioinspired design." . . "Presential"@en . "FALSE" . . "Basics of automation"@en . . "4" . "Basic concepts of control theory. Types and structures of control\nsystems. Structure of automatic control sys-tem. Elements of auto-\nmation systems. Modelling of objects and elements of automatics.\nOperator transmittance, spectral, state space. Controllability and\nobservability. Time and frequency characteristics. Stability - stability\ncriteria. Quality of regulation processes - criteria of regulation qual-\nity. Types of correction and types of regulators. Synthesis of control\nsystems by classical methods. Impulse control. Discrete transmit-\ntance of impulse control system. Digital control - basic structures.\nLogic and sequential control. Technology of automation systems:\nmeasuring devices (angle position sensors), regulators (control-\nlers), and actuators (setting and executive elements). Automated\nand robotic systems. Structures of 1st, 2nd and 3rd generation ro-\nbots. Simulation methods of dynamic systems study" . . "Presential"@en . "TRUE" . . "Basics of mechanical engineering 2"@en . . "2" . "Characteristics, classification and applications and design of sliding\nand rolling bearings. Bearing materials. Calculation and principles\nof bearing selection. Probability of damage on the example of rolling\nbearings. Mechanisms, types and applications.\nMethods of analysing kinematics and dynamics of mechanisms.\nKinematic analysis of plane and spatial mechanisms. Synthesis of\nmechanisms. Basic principles of modelling in the environment of\ncomputer-aided design, construction and drafting (CAD). Basic\nknowledge of databases. Geometric analysis of machine part mod-\nels. Concurrent and conceptual design. Collaborative design using\nCAD systems. Visualisation and simulation of product operation in\nCAD systems." . . "Presential"@en . "FALSE" . . "Basics of mechanical engineering 2"@en . . "2" . "Characteristics, classification and applications and design of sliding\nand rolling bearings. Bearing materials. Calculation and principles" . . "Presential"@en . "FALSE" . . "Ai robotics"@en . . "6" . "no data" . . "Presential"@en . "FALSE" . . "Embodied intelligence"@en . . "6" . "no data" . . "Presential"@en . "FALSE" . . "Robotics"@en . . "5" . "no data" . . "Presential"@en . "TRUE" . . "Autonomous mobile robots"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Micro and nano robotics"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Autonomous mobile robots"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Micro and nano robotics"@en . . "5" . "no data" . . "Presential"@en . "FALSE" . . "Basics of automation and control 1"@en . . "4" . "Basic introduction to the concept of Control Systems. Definition and interpretation of terms: CONTROL SYSTEM, FEEDBACK CONTROL, STABILITY of the system. Introduction to mathematical modelling -Laplace Transform as analysis and design tool for Control Systems. Transient and Frequency response analyses. Stability system analyses. The objective of the course is to gain the following abilities:\n - ability to transform the functions using Laplace transform,\n - ability to describe the control system in Laplace domain,\n - ability to create and simplify the block diagrams of controled objects,\n - ability to evaluate the typical system responses for standard inputs,\n - ability to apply basic stability criteria" . . "Presential"@en . "TRUE" . . "Autonomous robotics"@en . . "no data" . "N.A." . . "no data"@en . "TRUE" . . "Robotics and artificial intelligence in space engineering"@en . . "6" . "The course is mainly divided into three parts: \nPart I: Elements of robotics. The basic elements of Robotics are explained by referring to the manipulator, i.e., the \nkinematics along with the Denavit-Hartenberg parameters and the homogeneous roto-translation representation, the \ndifferential kinematics, the statics, and the dynamics. Moreover, the trajectory planning will be considered by using \nboth traditional methods and advanced methods based on meta-heuristic optimization (e.g., the Particle Swarm \nOptimization). All the previous elements will be used to introduce some basic control algorithms. \nPart II: Elements of Artificial Intelligence and Machine Learning. The basic elements of artificial intelligence and \nmachine learning are explained, and examples related both to robotics and space exploration will be considered. \nSpecifically, some basic elements for dealing with collection and pre-processing of data will be discussed. Then, simple \nalgorithms from machine learning will be addressed, such as the random forest or the support vector machines. \nConvolutional neural networks will be described, also taking into account the possibility to put such algorithm on-board \nfor autonomous satellites. Innovative recognition and \"detection\" algorithms on neural networks and/or on features \nextraction and latest generation matching techniques on EO / IR and SAR images. Examples dealing with remote \nsensing and space exploration will be shown. Finally, GAN architectures will be presented. \nPart III: New algorithms for navigation of space systems based on AI. Starting from optical and infrared mavigation, \nsensor errors, as aberration, boresight, noise input, will be discussed, in order to explain elements of optical and infrared \ntracking systems (e.g., missile seekers). Finally, AI image enhancement algorithms to increase the performance of an \nelectro-optical sensor and algorithms for super-resolving the image / object with single will be described." . . "Presential"@en . "FALSE" . . "Artificial intelligence in autonomous control systems"@en . . "6" . "Not found" . . "Presential"@en . "TRUE" . . "Aerial robotics"@en . . "10.00" . "Your learning on this unit\nAn overview of content\nWithin this unit, students will learn fundamental skills such as flight dynamics, control and avionics within the context of aerial robotics systems and applications. In additional to the legal requirements for UAV operations, students will be introduced to the use of software simulation tools for flight planning and algorithm development. These will include examples of flight dynamics models, sensor models and control systems, and be complemented with disruptive technologies such as autonomous navigation and bio-inspiration.\n\nHow will students, personally, be different as a result of the unit?\nStudents will have applied their fundamental understanding of dynamics and control to the design and operation of UAVs. They will also have extended their technical understanding in these areas and will have a clear overview of practical flight testing and evaluation.\n\nLearning Outcomes\n\nOn successful completion of the unit, students will be able to:\n\nidentify legal requirements for aerial robotics operations within UK airspace;\ndescribe typical aerial robotics systems and applications;\nconduct outline planning for a typical UAV operation within UK airspace;\nexplain the basis of feedback control systems for UAVs and their role in flight dynamics and guidance;\napply a typical route planning algorithm to a representative software simulation;\ncarry out a design trade-off study for a new aerial robotics platform." . . "Presential"@en . "FALSE" . . "Autonomous flight of micro air vehicles"@en . . "4.00" . "no data" . . "Presential"@en . "FALSE" . . "Physical interaction for aerial and space robots"@en . . "4.00" . "no data" . . "Presential"@en . "FALSE" . . "Space robotics project"@en . . "6.00" . "Learning outcomes\n\nBased on a conceptual design, students learn to develop and test a space robotics system in detail. It This is based on a draft concept, which is first examined. Building on this, the students learn a plan\nfor the development and integration of the system to be created and carried out. Creating and adhering to a test plan will also be important conveyed to the students.\nFurthermore, students learn to classify their own work within the performance of a project team and with others\nto work together.\nTeaching content\n\nAs part of the module, a design analysis of a system concept is first carried out. Based on this, within the framework of\nA detailed draft was developed using several work packages and the development of the system was advanced.\nAfter conducting reviews, the system is manufactured and integrated up to at least prototype status. Of The module also includes the creation of a test plan and the execution and evaluation of final tests." . . "Presential"@en . "FALSE" . . "Modern methods for life calculation of mechanical structures"@en . . "5.00" . "Learning Outcomes\nSuccessful completion of the course will lead the students to\n- understand and apply the state-of-the-art methods for determining the lifetime of engineering components subject to cyclic loading with constant amplitudes as well as to stochastic cyclic loading with variable mean loads and load amplitudes\n- determine the strength / fatigue life of engineering components (except welded structures) in dependence of the applied loading by means of calculational methods\n- assess the advantages, calculationa accuracy and the application limits of the tought calcualtional methods\n- determine the influence of materials, treatments and enviroment on the fatigue strength by means of experiments, calcualtion algorithms and models.\nGeneral Competences\nApply knowledge in practice\nRetrieve, analyse and synthesise data and information, with the use of necessary technologies\nAdapt to new situations\nMake decisions\nWork autonomously\nWork in teams\nWork in an interdisciplinary team\nGenerate new research ideas\nAdvance free, creative and causative thinking\nCourse Content (Syllabus)\nLoad sequences and load spectra, creation of load spectra according to the rainflow, range-pair and level crossing counting methods.\nModern fatigue life calculation methods for engineering components: Nominal Stress Concept, Nominal Stress Concept, Local Strain Approach, Fracture Mechanics Concepts, all including exercises." . . "Hybrid"@en . "TRUE" . . "Cae – simulation of mechanical structures"@en . . "5.00" . "Learning Outcomes\nAfter successful completion of the course, students should be able to:\n(a) Create accurate Finite Element models\n(b) To work efficiently with state-of-the-art pre- and postprocessing software\n(c) To evaluate the results\nGeneral Competences\nApply knowledge in practice\nRetrieve, analyse and synthesise data and information, with the use of necessary technologies\nMake decisions\nGenerate new research ideas\nDesign and manage projects\nBe critical and self-critical\nAdvance free, creative and causative thinking\nCourse Content (Syllabus)\n3D-surface definition using CAD systems. Databases of the CAD systems and neutral file standards (IGES, VDA-FS, STEP, SET). FE-Descritization of 3D-structures and elements quality evaluation. Applying boundary conditions and loads. FEA modules for structural analysis, with applications in automotive body design. Post processing, results analysis and structure optimization." . . "Hybrid"@en . "TRUE" . . "Tribology"@en . . "5.00" . "no data" . . "Presential"@en . "FALSE" . . "Numerical control of machine tools"@en . . "5.00" . "no data" . . "Presential"@en . "FALSE" . . "Spatial mechanisms-industrial robots"@en . . "5.00" . "no data" . . "Presential"@en . "FALSE" . . "Diagnostic control of machine tools"@en . . "5.00" . "no data" . . "Presential"@en . "FALSE" . . "Autonomous robotic systems"@en . . "6.0" . "Operating autonomously in unknown and dynamically changing environments is a core challenge that all robotic systems must solve to work successfully in industrial, public, and private areas. Currently popular systems that must demonstrate such capabilities include self-driving cars, autonomously operating drones, and personal robotic assistants. In this course, students obtain deep knowledge in creating autonomous robotic systems that can operate in and manipulate unknown and dynamically changing environments by autonomously planning, analysing, mapping, and modelling of such environments. Students learn to approach these challenging tasks through three main techniques: swarm intelligence, model-based probabilistic frameworks, and (mostly) model-free techniques from artificial evolution and machine learning.\n\nPrerequisites\nNone.\n\nDesired Prior Knowledge: Discrete Mathematics, Linear Algebra, Probabilities and Statistics, Data Structures and Algorithms, Machine Learning, Search Techniques.\n\nRecommended reading\nFloreano and Nolfi (2000), Evolutionary Robotics, The MIT press. ISBN-13: 978-0262640565.\nDario Floreano und Claudio Mattiussi (2008), Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies, ISBN-13: 978-0262062718\n\n\nMore information at: https://curriculum.maastrichtuniversity.nl/meta/463161/autonomous-robotic-systems" . . "Presential"@en . "FALSE" . . "Space robotic systems"@en . . "6.0" . "The course provides the required knowledge to cope with the design of robotic space systems. The main objective is the study of the guidance, navigation and control systems for missions of on-orbit-servicing, rendez-vous and docking, and planetary exploration." . . "Presential"@en . "TRUE" . . "Robotics"@en . . "4.0" . "Aims\n\nThis course is an introduction to Intelligent Robotic Systems, i.e., machines that move (themselves and/or objects in their environment) and sense what is going on in their (immediate) neighbourhood, in order to achieve a given goal under uncertain environment conditions.\n\nApplying AI techniques to a physical system poses challenges that are not apparent in other contexts. This course aims to teach how one casts an embodied-agent problem to a form that lends itself to an AI solution, for instance by choosing AI techniques, sensor/data representations and motor command schemes that are synergetic with one another.\n\nThis course will cover both \"classical\" AI techniques that are easily parametrized by an expert, and techniques that are learned from data. We will study the applicability of both approaches and discuss how to judiciously choose one or the other based on the nature of the task.\n\nSince robotics is about integrating the best things from several research areas (mechanics, computer science, geometry, artificial intelligence, ...), relationships with other courses often occur, but we avoid overlaps as much as possible. The students are intensively stimulated to think and discuss as a researcher.\n\nDuring the course, students\n\nidentify problems that lend themselves to a robot AI solution and decide whether a “classical” or data-driven solution should be preferred,\ncast an embodied-agent problem to a form that lends itself to an AI solution,\ngenerate an intelligent robot behavior (conceptual or in software):\nExtract information from sensor streams (e.g., object/people identity/position, body postures, 3D room and object structures),\nControl robot actuators,\nLearn useful sensorimotor behaviors (e.g., mobility or grasping),\nlearn to analyse robotics applications from a system-level point of view, since robotics is very much a science of integration.\nare stimulated to develop a critical, research-oriented attitude.\n\nContent\n\nThis course is organized as guided self study: there is only a limited number of lectures in class (to explain and discuss the fundamental concepts of robot AI). For the rest of the course the students work on problems of their own choice. Collaboration in groups of maximally three students is encouraged.\n\nThe course has no organized examination session: it uses continuous evaluation, based on the students' reports, to which feedback is provided by the lecturer and all other students. Reports and the feedback to them are public to all participating students, and become an inherent part of the \"course material\". In a final individual discussion session with the lecturer, each student is expected to present the material in a relevant academic research paper in a very critical way, and to show creativity in identifying appropriate applications, open problems, or inherent limitations in the studied material.\n\nThe concept of the course allows to adapt its contents to the interests and background of the students.\n\nMore information can be found on the course's webpage: https://renaud-detry.net/teaching/h02a4a/" . . "Presential"@en . "FALSE" .