Constrained Differential Dynamic Programming Solver for Trajectory Optimization and Model Predictive Control
-
Updated
May 22, 2024 - C++
Constrained Differential Dynamic Programming Solver for Trajectory Optimization and Model Predictive Control
iterative Linear Quadratic Regulator with constraints.
Gradient-based trajectory optimisation toolbox that speeds up trajectory optimisation by only computing dynamics derivatives at key-points with finite-differencing. Remainder of derivatives are approximated via interpolation.
ILQR (Iterative Linear Quadratic Regulator)
Project for Dynamical System Theory exam - Publication for IROS 2022 Conference
SIA - C++/Python library for model-based stochastic estimation and optimal control
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.
iLQR for a 3D quadrotor model
Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation.
First homework for the RL class
Code supporting the WAFR paper "A Performance Analysis of Differential Dynamic Programming on a GPU," and the ICRA workshop follow on work deploying the algorithm onto robot hardware.
Trajectory optimization (indirect with iLQR, direct with SQP), model predictive control, and additional tools for quantum optimal control.
MPC, iLQR, Stanley, Pure Pursuit Controllers in AWSIM using ROS2
Non-linear trajectory optimization via iLQR/DDP.
A Julia package for constrained iterative LQR (iLQR)
An optional control algorithm, iterative Linear Quadratic Regulator, implementation using Julia.
Repository of Reinforcement Learning projects done during the course @sapienza
LQR and iLQR controllers for a 2D quadrotor.
Add a description, image, and links to the ilqr topic page so that developers can more easily learn about it.
To associate your repository with the ilqr topic, visit your repo's landing page and select "manage topics."