# Computational Design and Dynamics of Soft Systems ·

This is a repository that contains the source code for generating the lecture notes, handouts, exercises for the computational lab-sessions of the course offered at UIUC.

## Description

This course provides a hands-on introduction to modern modeling and simulations techniques for heterogeneous structures made of assemblies of soft, elastic slender elements. Such systems are ubiquitous in nature, from animal musculoskeletal architectures to ‘birds-nest’ composite materials. They are also becoming increasingly relevant in robotics. Students will implement in python their own Cosserat rods-based solver. The developed solver will be then coupled with evolutionary optimization techniques for design, and reinforcement learning for control.

## Prerequisities

None.

## Content

- Introduction to modeling and simulation for inverse design
- Basics of evolutionary strategies
- Covariance Matrix Adaptation – Evolution Strategy (CMA-ES)
- Basic concepts of Reinforcement Learning
- Soft robotic modeling with Cosserat rods
- Space and time discretization
- Application to snake slithering
- Complex creatures modeling
- Examples of potential experimental applications

## Organization

The course is organized in three modules listed below.

- Python for engineers
- Non-linear stochastic optimization
- Modeling of soft systems
- Visualizing soft-system dynamics

## Setup

To get started with the course, please consult this folder.