Project for Dynamical System Theory exam - Publication for IROS 2022 Conference

First homework for the RL class

This repo contains all the praticals/homeworks assigned during the Reinforcement Learning course held by Prof. Roberto Capobianco at the AI & Robotics Master's Degree at University of Sapienza @ Rome, Italy.

Optimal control Rust library

ILQR controller acting on a two link arm model of the human arm to demonstrate reaching between points in a 2d plane

Different approaches to control the cart and pole system from LQR to Reinforcement learning algorithm as SARSA and Q-learning

A C++ implementation of a MPC framework for the humanoids using iLQR to solve the optimal control problem, leveraging the Pinocchio-Casadi library for efficient rigid body dynamics and analytical derivatives.

An optional control algorithm, iterative Linear Quadratic Regulator, implementation using Julia.

Repository of Reinforcement Learning projects done during the course @sapienza

Python implementation of several planning and control algorithms with interactive visualization and simulation capabilities.

Augmented linear-quadratic motion planner

A Multi-Agent Solving Library

Trajectory optimization for 2 degrees of freedom arm

Optimal Control via Combined Inference and Numerical Optimization

Trajectory optimization (indirect with iLQR, direct with SQP), model predictive control, and additional tools for quantum optimal control.

Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation.

Mujoco derivatives in python

Differential Dynamic Programming python implementation for a cartpole system

Diffilqrax is an open-source Python library for differentiable iLQR and LQR in JAX

An implementation of the Iterative Linear Quadratic Regulator (iLQR) method to control nonlinear dynamical systems