Computational motor control

CS-432

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Course summary

Computational Motor Control

Teacher: Prof. Auke Ijspeert, auke.ijspeert@epfl.ch

Assistants:

Andrea.Ferrario@epfl.ch (Main assistant),
Jonathan.Arreguitoneill@epfl.ch
Alessandro.Crespi@epfl.ch
Qiyuan.Fu@epfl.ch
Alessandro.Pazzaglia@epfl.ch
Chuanfang.Ning@epfl.ch
Lixuan.Tang@epfl.ch
Lisa.Schneider@epfl.ch
Nina.Lahellec@epfl.ch
Sebastien.Chahoud@epfl.ch
Tim.Lucking@epfl.ch

Description

The course gives (1) a review of different types of numerical models of control of locomotion and movement in animals, from fish to humans, (2) a presentation of different techniques for designing models, and (3) an analysis of the use and testing of those models in robotics and neuroprosthetics.

Content:

General concepts: Importance of numerical models in a scientific approach, introduction to nonlinear dynamical systems and neural network models.
Numerical models of motor systems : Neural network models of control of locomotion, rhythm generation in central pattern generators, reflexes, force fields, sensory-motor coordination, and balance control.
Numerical models of the musculo-skeletal system: muscle models, biomechanical models of locomotion, gait classification, applications to bio-inspired robots.
Numerical models of arm movements: invariants of human arm movements, different hypotheses about human motor control: inverse models and equilibrium point hypothesis. Muscle synergies.
Numerical models of sensory systems : Proprioception and vestibular system. Visual processing in the retina, salamander and primate visual systems, applications to machine vision.
Neuroprosthetics: short overview of current developments, analysis of how modeling can be used to improve interfaces between machines and the central nervous system
Numerical exercises: The course will also involve numerical exercises in which students will develop their own numerical simulations of sensory-motor systems in Python and in a dynamical robot simulator (with weekly sessions with assistants and the professor).•

When and Where

Theory (lectures): Thursdays 10:15 - 12:00, in AAC231 https://plan.epfl.ch/?room==AAC%202%2031
Laboratory (practicals): Thursdays 13:15 - 15:00, in INF2 https://plan.epfl.ch//?room==INF%202

Course Prerequisites

Basic programming skills
Basic linear algebra and analysis (dynamical systems)
Nice to have: minimal knowledge of Python and of GIT

Course Format

The course will involve lectures, modeling exercises, and a mini project. The modeling exercises and mini project will be carried out using Python in groups of three students on your own laptops (we will give instructions on how to install Python). The course marks will depend on the written reports for the modeling exercises (60% of the final grade), and on a written exam (40% of the final grade).

The written exam will take place on May 15, 10:15-12:15 (rooms AAC231, normal lecture room for students with last names from A to K, and SG 0211 for students with last names from L to Z). Please try to arrive for 10:05, and wait until we open the doors. See the forum for more instructions.

Course Communication

Communication with the assistants is preferably done by the Practicals forum, see below.

Queries related to the lectures should be posted on the Lectures forum.

Week 1

20.02.2025 Week 1: Introduction

Overview of the organization and content of the course. Presentation of how numerical models are used in animal motor control.

In the afternoon, please bring your laptops for the practical presentation, including Python installation and intro.

Week 2

27.02.2025 Week 2: Introduction to dynamical systems

Ordinary differential equations (ODEs), solving of ODEs (analytically, numerically, geometrically), definition of stability, linear systems

Week 3

06.03.2025 Week 3: Introduction to nonlinear dynamical systems, part II

Stability of nonlinear systems, Graphical representations of dynamical systems, Oscillators, limit cycle behavior, Systems of coupled oscillators.

Note: because of the problem of the beamer, I included a recording for the previous year for the final part.

Week 4

13.03.2025 Week 4: Models of neurons

Biological neurons, McCulloch and Pitts neurons, Perceptron, Backpropagation, Leaky integrator neuron models.

Week 5

20.03.2025 Week 5: Models of neurons (continued) and of muscles

Integrate-and-fire neuron model, Hodgkin-and-Huxley neuron model, muscles and muscle models.

Week 6

27.03.2025 Week 6: Locomotion and models of lamprey swimming

General principles of animal locomotion, central pattern generators, lamprey swimming circuit, zebrafish swimming circuit, phase oscillator models of the lamprey swimming circuit

Week 7

03.04.2025 Week 7: Lamprey (continued) and salamander locomotion

Week 8

10.04.2025 Week 8: Gaits + Models of reflexes and sensory feedback

Week 9

27.04.2025 Week 9: Models of the visual system

Visual systems in the salamander and in primates. Concepts of receptive fields, center-surround responses, tuning curves, fine vs coarse coding, efferent copy, and multi-layered processing.

Week 10

01.05.2025 Week 10: Models of arm movements

Invariants of arm movements, different school of thoughts about arm control, population-based coding

Week 11

08.05.2025 Week 11: Only practicals

Because Auke Ijspeert is at a conference, there is no lecture this week, only the practicals. Teaching assistants will come like usual at 13:15.

Week 12

15.05.2025 Week 12: Exam

Written exam from 10:15 to 12:15 in the rooms AAC231, normal lecture room for students with last names from A to K, and SG 0211 for students with last names from L to Z. Please try to arrive for 10:05, and wait until we open the doors. See the forum for more instructions.

Practicals like normal at 13:15