4 embodied-AI and robotics papers accepted at NeurIPS 2021, 3 with code.4 篇被 NeurIPS 2021 接收的具身智能与机器人论文，其中 3 篇附代码。
Feed papers are listed when their arXiv comment says they were accepted (e.g. 'Accepted to CoRL 2026'); papers that do not say so are missing, and the list grows as authors post camera-ready versions. Curated entries carry a hand-checked venue.日常 arXiv 论文仅在其 arXiv 备注写明已被接收（如 “Accepted to CoRL 2026”）时列入；未注明的论文不会出现，列表会随作者上传终稿而增加。精选条目的会议/期刊信息经过人工核对。
JAX physics engine that runs thousands of environments in parallel on GPU/TPU together with the RL training loop, cutting locomotion training from hours to minutes.基于 JAX 的物理引擎，在 GPU/TPU 上与强化学习训练循环一起并行运行数千个环境，把运动控制训练从数小时缩短到数分钟。
@misc{freeman2021brax,
title = {{Brax: A Differentiable Physics Engine for Large Scale Rigid Body Simulation}},
author = {C. Daniel Freeman and Erik Frey and Anton Raichuk and Sertan Girgin and Igor Mordatch and Olivier Bachem},
year = {2021},
eprint = {2106.13281},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2106.13281},
}
Recasts RL as sequence modeling — a GPT-style model predicts actions conditioned on the desired return; an early bridge between transformers and control.把强化学习改写成序列建模：GPT 式模型以期望回报为条件预测动作；是 Transformer 与控制结合的早期代表。
@misc{chen2021decision,
title = {{Decision Transformer: Reinforcement Learning via Sequence Modeling}},
author = {Lili Chen and Kevin Lu and Aravind Rajeswaran and Kimin Lee and Aditya Grover and Michael Laskin and Pieter Abbeel and Aravind Srinivas and Igor Mordatch},
year = {2021},
eprint = {2106.01345},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2106.01345},
}
Adds fast rigid-body physics and an interactive apartment dataset (ReplicaCAD) to Habitat, plus a home-rearrangement benchmark for mobile manipulators.为 Habitat 加入快速刚体物理与可交互公寓数据集 ReplicaCAD，并提出面向移动操作机器人的家居物品重排基准。
@misc{szot2021habitat,
title = {{Habitat 2.0: Training Home Assistants to Rearrange their Habitat}},
author = {Andrew Szot and Alex Clegg and Eric Undersander and Erik Wijmans and Yili Zhao and John Turner and Noah Maestre and Mustafa Mukadam and Devendra Chaplot and Oleksandr Maksymets and Aaron Gokaslan and Vladimir Vondrus and Sameer Dharur and Franziska Meier and Wojciech Galuba and Angel Chang and Zsolt Kira and Vladlen Koltun and Jitendra Malik and Manolis Savva and Dhruv Batra},
year = {2021},
eprint = {2106.14405},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2106.14405},
}
1,000 3D scans of real indoor spaces for Habitat; the main scene set behind ObjectNav and many embodied navigation benchmarks.1000 个真实室内空间的 3D 扫描，供 Habitat 使用；ObjectNav 等众多具身导航基准的主要场景集。
@misc{ramakrishnan2021habitat,
title = {{Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI}},
author = {Santhosh K. Ramakrishnan and Aaron Gokaslan and Erik Wijmans and Oleksandr Maksymets and Alex Clegg and John Turner and Eric Undersander and Wojciech Galuba and Andrew Westbury and Angel X. Chang and Manolis Savva and Yili Zhao and Dhruv Batra},
year = {2021},
eprint = {2109.08238},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2109.08238},
}