Ingredients for Medical Robotics Research

Despite the increasing prevalence of robotic surgical systems in operating rooms, little work has been done to automate their tasks or capabilities. Assist is an open-source interface to machine learning tasks that aims to provide medical researchers with the ability to quickly prototype and train machine learning algorithms in simulation, before deploying them to real-world settings.

Getting Started

This repository includes simulated robotic environments and tools for use in teaching agents various tasks required for medical procedures and surgeries. The environments are built using MuJoCo and Gym, meaning that both of those packages and their dependencies are required prior to using Assist.

Setup and Installation

Clone this repository on your system and install Assist using the following commands:

git clone https://github.com/cyrilzakka/gym-assist
cd gym-assist
pip install -e .

Testing the Environments

import gym
import gym_assist

env = gym.make('Suture-v0')
env.reset()

for _ in range(1000):
    env.render()
    env.step(env.action_space.sample()) #take a random action

env.close()

Citation

@misc {
      Cyrilzakka,
      author = {Zakka, Cyril},
      title = {Ingredients for Medical Robotics Research},
      year = {2019},
      publisher = {GitHub},
      journal = {GitHub repository},
      howpublished = {\url{https://github.com/cyrilzakka/gym-assist}},
}