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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

Instructors

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

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Summary

Lectures

Instructors

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

Ontological neighbourhood

Mechanical engineering

Robotics: Topics in robotics

Systems science and engineering

Systems theory: Chaos theory

Lectures in this course (17)

Learning and Adaptive Control for Robots: Overview and Path Planning

Explores learning and adaptive control for robots, focusing on challenges, path planning with dynamical systems, and real-time planning applications.

Acquiring Data for Learning: Modern Approaches and Challenges

Explores modern approaches and challenges in acquiring data for learning optimal controllers through demonstrations and data-driven methods.

Learning and Adaptive Control for Robots

Explores learning, adaptive control, cutting soft tissue, and robotic implementation for robots.

Dynamical Systems: Equilibrium Points and Stability

Covers dynamical systems, equilibrium points, stability analysis, and phase plots using examples like the pendulum system.

Why Standard ML is Not Sufficient: Learning and Adaptive Control

Delves into the challenges of using standard ML for stable robot control.

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