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[[Project Website]](https://med-air.github.io/SurRoL/)\n\nIEEE RA-L'23 [Human-in-the-loop Embodied Intelligence with Interactive Simulation Environment for Surgical Robot Learning](https://arxiv.org/abs/2301.00452) \u003cbr\u003e\nICRA'23 [Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical Robot](https://arxiv.org/abs/2302.09772) \u003cbr\u003e\nISMR'22 [Integrating artificial intelligence and augmented reality in robotic surgery: An initial dVRK study using a surgical education scenario](https://arxiv.org/abs/2201.00383) \u003cbr\u003e\nIROS'21 [SurRoL: An open-source reinforcement learning centered and dVRK compatible platform for surgical robot learning](https://arxiv.org/abs/2108.13035)\n\n\n\u003cp align=\"center\"\u003e\n   \u003cimg src=\"resources/img/surrol-overview.png\" alt=\"SurRoL\"/\u003e\n\u003c/p\u003e\n\n## Features\n\n- [dVRK](https://github.com/jhu-dvrk/sawIntuitiveResearchKit/wiki) compatible [robots](./surrol/robots).\n- [Gym](https://github.com/openai/gym) style [API](./surrol/gym) for reinforcement learning.\n- Ten surgical-related [tasks](./surrol/tasks).\n- Various object [assets](./surrol/assets).\n- Based on [PyBullet]((https://github.com/bulletphysics/bullet3)) for physics simulation.\n\n## Installation\n\nThe project is built on Ubuntu with Python 3.7,\n[PyBullet](https://github.com/bulletphysics/bullet3),\n[Gym 0.15.6](https://github.com/openai/gym/releases/tag/0.15.6),\nand evaluated with [Baselines](https://github.com/openai/baselines),\n[TensorFlow 1.14](https://www.tensorflow.org/install/pip).\n\n### Prepare environment\n\n1. Create a conda virtual environment and activate it.\n\n    ```shell\n    conda create -n surrol python=3.7 -y\n    conda activate surrol\n    ```\n\n2. Install gym (slightly modified), tensorflow-gpu==1.14, baselines (modified).\n\n### Install SurRoL\n\n```shell\ngit clone https://github.com/med-air/SurRoL.git\ncd SurRoL\npip install -e .\n```\n\n## Get started\n\nThe robot control API follows [dVRK](https://github.com/jhu-dvrk/dvrk-ros/tree/master/dvrk_python/src/dvrk)\n(before \"crtk\"), which is compatible with the real-world dVRK robots.\n\nYou may have a look at the jupyter notebooks in [tests](./tests).\nThere are some test files for [PSM](./tests/test_psm.ipynb) and [ECM](./tests/test_ecm.ipynb),\nthat contains the basic procedures to start the environment, load the robot, and test the kinematics.\n\nWe also provide some [run files](./run) to evaluate the environments using baselines.\n\n## Citation\n\nIf you find the paper or the code helpful to your research, please cite the project.\n\n```\n@inproceedings{xu2021surrol,\n  title={SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning},\n  author={Xu, Jiaqi and Li, Bin and Lu, Bo and Liu, Yun-Hui and Dou, Qi and Heng, Pheng-Ann},\n  booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},\n  year={2021},\n  organization={IEEE}\n}\n```\n## License\n\nSurRoL is released under the [MIT license](LICENSE).\n\n## Acknowledgement\n\nThe code is built with the reference of [dVRK](https://github.com/jhu-dvrk/sawIntuitiveResearchKit/wiki),\n[AMBF](https://github.com/WPI-AIM/ambf),\n[dVRL](https://github.com/ucsdarclab/dVRL),\n[RLBench](https://github.com/stepjam/RLBench),\n[Decentralized-MultiArm](https://github.com/columbia-ai-robotics/decentralized-multiarm),\n[Ravens](https://github.com/google-research/ravens), etc.\n\n\n## Contact\nFor any questions, please feel free to email \u003ca href=\"mailto:qidou@cuhk.edu.hk\"\u003eqidou@cuhk.edu.hk\u003c/a\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmed-air%2FSurRoL","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmed-air%2FSurRoL","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmed-air%2FSurRoL/lists"}