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Talk1 h 5 min

REMOTE - Robotics activities at CERN - Optimisation techniques, kinematics and designs

Hannes Gamper · CERN

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Optimisation techniques, kinematics and designs

This talk will give an overview about the mathematical description of rigid mechanical structures in terms of kinematics and dynamics, such that the derived models can be used to predict the behaviour and thus control these systems or robots. An emphasis will be put on a very common problem in robotics: finding the necessary configuration of a robot, such that its end-effector reaches the desired position, called inverse kinematics. Furthermore, it will be demonstrated how to use the derived kinematic and dynamic models for design optimization of the mechanical structure, including the optimization of the topology, geometry, torque, error propagation and collision avoidance. The basics of trajectory generation will also be introduced, particularly to generate smooth trajectories that can allow for stable motion of robotic systems.

Short bio Hannes Gamper

BSc in Mechatronics (Specifically Mathematic Modelling & Control Theory) at Johannes Kepler University (Austria)

MSc (~30%) in Computer Science at California State University (USA)

MSc (~70%) in Robotics at Johannes Kepler University (Austria)

Fellow at NASA's Jet Propulsion Laboratory (Systems Engineering for Europa Mission (Lander for Jupiter Moon Europa))

PhD Candidate at CERN since 2019 (Working on a Robotic System for the Future Circular Collider)

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The talk

  1. REMOTE - Robotics activities at CERN - Optimisation techniques, kinematics and designs 2022-01-27 · 1 h 5 min · CERN's player

Credits and licence

Institution
CERN
Department
Academic Training Lecture Regular Programme,2021-2022
Speaker
Hannes Gamper
Year
2022
Level
Graduate
Language
English
Subjects
Engineering
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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