Objectives of Programme's Learning Outcomes

• Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out mechanical engineering missions, using their expertise and adaptability.
• Master and appropriately mobilise knowledge, models, methods and techniques specific to mechanical engineering.
• Study a machine, equipment, system, method or device by critically selecting theories and methodological approaches, and taking into account multidisciplinary aspects.
• Identify and discuss possible applications of new and emerging technologies in the field of mechanical engineering.
• Communicate and exchange information in a structured way - orally, graphically and in writing, in French and in one or more other languages - scientifically, culturally, technically and interpersonally, by adapting to the intended purpose and the relevant public.
• Argue to and persuade clients, colleagues, teachers and boards, both orally and in writing.
• Select and use written communication methods and materials, graphically or orally, adapted to the intended purpose and the relevant public.
• Use and produce scientific and technical documents (reports, plans, specifications, etc.) adapted to the intended purpose and the relevant public.

Learning Outcomes of UE

 - For AA I-MRDV-099 Industrial Robotics :
* Get acquainted with the fundamentals of robotics: geometry, kinematics, dynamics and control.
* Get an overview of the specific issues and challenges related to the application of robotics in the industry in terms of mechanical design, sensing, control and safety.
* Get an overview of robot programming.

- For AA I-ISIA-0xx Computer Vision :
* Develop image processing techniques, together with a critical analysis of the problem;
* Apply image analysis, segmentation and feature extraction techniques
* Apply classification and machine learning techniques (deep learning)
 

UE Content: description and pedagogical relevance

 - For AA I-MRDV-099 Industrial Robotics :
Introduction: industrial robots, the market.
* Robot Kinematics: degrees of freedom, 3D rigid-body kinematics reminders, direct and inverse geometric and kinematic models, Denavit-Hartenberg parameters, manipulability, differential kinematics.
* Robot Dynamics: equations of motion, contributions of inertia, gravity, friction, direct and inverse dynamic models of robots.
* Actuation: electrical motors in robotics, mechanical transmissions and sensors.
* Control of industrial robots: joint/operational space control, decentralized control, position/velocity feedback, feedforward compensation, gravity compensation, inverse dynamic control, force control.
* Trajectory planning
* Robots and industrial vision systems.

- For AA I-ISIA-0xx Computer Vision :
* Image Processing, Image acquisition; lowlevel processing, filtering, transforms; image segmentation and registration;
* Deep Learning


 

Prior Experience

Not applicable