Zero Order Optimization Techniques for Robotics

This repository contains all the code necessary to reproduce the experiment of the paper: "An Introduction to Zero-Order Optimization Techniques for Robotics". The project is divided in two main sections:

• The traj_opt folder contains the trajectory optimization results.
• The rl folder contains the reinforcement learning results.

Contributors

• Armand Jordana (NYU): main developer and manager of the project
• Jianghan Zhang (NYU): main developer of the trajectory optimization benchmark
• Joseph Amigo (NYU): main developer of the RL benchmark
• Ludovic Righetti (NYU): project instructor