The Official Code for "Object-Oriented Option Framework for Robotics Manipulation in Clutter", which is published at IROS 2023.
O3F
|- gym: modified gym based on our needs
|- models: directory for saving by-produc
626E
t models
|- stable_baselines3: modified stable-baselines3 (sb3) based on our needs
|- train_oe.py: code for Option Executor (OE) training
|- train_op.py: code for Option Planner (OP) training
- Please finish the following steps to install conda environment and related python packages
- Conda Environment create
conda create --name <env_name> --file spec-list.txt
- Package install
pip install -r requirements.txt
- The environments used in this work require MuJoCo as dependency. Please setup it following the instructions:
- Instructions for MuJoCo: https://mujoco.org/
We offer a fine-trained Option Executor (OE) model which Option Planner (OP) utilizes during training for testing.
models/execute.zip-
Training of OE
- Command
python train_oe.py
- The models of oe will be saved at
oe_model. - The tensorboard logs of oe will be saved at
oe_train.
-
Training of OP
- Command
python train_op.py
- The models of op will be saved at
op_model. - The tensorboard logs of op will be saved at
op_train.
@inproceedings{o3f/iros/pang,
author = {Jing-Cheng Pang and
Si-Hang Yang and
Xiong-Hui Chen and
Xinyu Yang and
Yang Yu and
Mas Ma and
Ziqi Guo and
Howard Yang and
Bill Huang},
title = {Object-Oriented Option Framework for Robotics Manipulation in Clutter},
booktitle = {{IEEE/RSJ} International Conference on Intelligent Robots and Systems,
{IROS}},
year = {2023}}