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Update overview page text for 1.5
snasiriany
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Nov 4, 2024
docs/overview.md
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| **robosuite** is a simulation framework powered by the [MuJoCo](http://mujoco.org/) physics engine for robot learning. It also offers a suite of benchmark environments for reproducible research. The current release (v1.4) features long-term support with the official MuJoCo binding from DeepMind. This project is part of the broader [Advancing Robot Intelligence through Simulated Environments (ARISE) Initiative](https://github.com/ARISE-Initiative), with the aim of lowering the barriers of entry for cutting-edge research at the intersection of AI and Robotics. | |||
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| **robosuite** is a simulation framework powered by the [MuJoCo](http://mujoco.org/) physics engine for robot learning. It also offers a suite of benchmark environments for reproducible research. The current release (v1.5) features support for diverse robot embodiments (including humanoids), custom robot composition, composite controllers (including whole body controllers), more teleoperation devices, photo-realistic rendering. This project is part of the broader [Advancing Robot Intelligence through Simulated Environments (ARISE) Initiative](https://github.com/ARISE-Initiative), with the aim of lowering the barriers of entry for cutting-edge research at the intersection of AI and Robotics. | |||
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| Data-driven algorithms, such as reinforcement learning and imitation learning, provide a powerful and generic tool in robotics. These learning paradigms, fueled by new advances in deep learning, have achieved some exciting successes in a variety of robot control problems. However, the challenges of reproducibility and the limited accessibility of robot hardware (especially during a pandemic) have impaired research progress. The overarching goal of **robosuite** is to provide researchers with: | |||
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remove the note about the pandemic? that's in the past now
docs/overview.md
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| @inproceedings{robosuite2020, | ||
| title={robosuite: A Modular Simulation Framework and Benchmark for Robot Learning}, | ||
| author={Yuke Zhu and Josiah Wong and Ajay Mandlekar and Roberto Mart\'{i}n-Mart\'{i}n and Abhishek Joshi and Soroush Nasiriany and Yifeng Zhu}, | ||
| author={Yuke Zhu and Josiah Wong and Ajay Mandlekar and Roberto Mart\'{i}n-Mart\'{i}n and Abhishek Joshi and Soroush Nasiriany and Yifeng Zhu and Kevin Lin}, |
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is this going to be the ordering? @yukezhu @zhuyifengzju pls comment
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We should follow our existing convention. New names should not be appended to the end. Instead, core members should be put in alphabetical order. See the footnote in our whitepaper: https://robosuite.ai/assets/whitepaper.pdf
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seems unrelated to this PR
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Updated @snasiriany |
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