Course

MICRO-462: Learning and adaptive control for robots

Summary

To cope with constant and unexpected changes in their environment, robots need to adapt their paths rapidly and appropriately without endangering humans. this course presents method to react within millisecunds.

Lectures

Instructor

Aude Billard

Expertise RoboticsMachine LearningArtificial IntelligenceHuman-Robot InteractionMechatronicsDynamical Systems ControlComputational Neuroscience Aude Billard is full professor and head of the LASA laboratory at the School of Engineering at the Swiss Institute of Technology Lausanne (EPFL), and the Director of the Swiss Innovation Booster on Robotics. Dr. Billard acts as the President of the IEEE Robotics and Automation Society (RAS), after serving in several roles in the administrative and executive committe

Official source

https://edu.epfl.ch/coursebook/en/learning-and-adaptive-control-for-robots-MICRO-462

Moodle Page

http://go.epfl.ch/MICRO-462

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Summary

Lectures

Instructor

Aude Billard

Official source

https://edu.epfl.ch/coursebook/en/learning-and-adaptive-control-for-robots-MICRO-462

Moodle Page

http://go.epfl.ch/MICRO-462

About this result

Lectures in this course (17)

Robot Learning and Control

Covers learning and adaptive control for robots, focusing on real-time reactivity and path planning using dynamical systems.

Acquiring Data for Learning

Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.

Introduction to Dynamical System

Introduces dynamical systems, equilibrium points, stability, vector fields, phase plots, and Lyapunov stability.

Learning control laws with DS

Explores learning control laws with Dynamical Systems for robots, focusing on regression problems and fitting techniques.

Stable Estimator of Dynamical System (SEDS)

Explores Stable Estimator of Dynamical Systems (SEDS) for robots, covering stability, modeling, optimization, and limitations.

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