从近30篇具身综述中!看领域发展兴衰(VLA/VLN/强化学习/Diffusion Policy等方向)

今天为大家整理了几十篇具身相关的综述,设计数据集、评测、VLA、VLN、强化学习、基础模型、DP等方向,为大家一览具身发展的路线,内容出自具身智能之心知识星球。

A Survey on Vision-Language-Action Models: An Action Tokenization Perspective.2025

论文链接:https://arxiv.org/pdf/2507.01925

A Survey on Vision-Language-Action Models for Autonomous Driving.2025

论文链接:https://arxiv.org/pdf/2506.24044

项目链接:https://github.com/JohnsonJiang1996/Awesome-VLA4AD

Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends.2025

论文链接:https://arxiv.org/pdf/2506.20966

项目链接:https://github.com/AoqunJin/Awesome-VLA-Post-Training

Foundation Models in Robotics: Applications, Challenges, and the Future.2025

论文链接:https://arxiv.org/pdf/2312.07843

项目链接:https://github.com/robotics-survey/Awesome-Robotics-Foundation-Models

Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes.2025

论文链接:https://www.arxiv.org/abs/2408.03539

A Survey on Diffusion Policy for Robotic Manipulation: Taxonomy, Analysis, and Future Directions.2025

论文链接:https://doi.org/10.36227/techrxiv.174378343.39356214/v1

项目链接:https://github.com/HITSZ-Robotics/DiffusionPolicy-Robotics

Embodied Intelligent Industrial Robotics: Concepts and Techniques.2025

论文链接:https://arxiv.org/pdf/2505.09305

项目链接:https://github.com/jackeyzengl/Embodied_Intelligent_Industrial_Robotics_Paper_List

Neural Brain: A Neuroscience-inspired Framework for Embodied Agents .2025

论文链接:https://arxiv.org/pdf/2505.07634

项目链接:https://github.com/CNJianLiu/Neural-Brain-for-Embodied-Agents

Vision-Language-Action Models: Concepts, Progress, Applications and Challenges.2025

论文链接:https://arxiv.org/pdf/2505.04769v1

A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI.2025

论文链接:https://arxiv.org/pdf/2505.01458

Multimodal Perception for Goal-oriented Navigation: A Survey.2025

论文链接:https://arxiv.org/pdf/2504.15643

Diffusion Models for Robotic Manipulation: A Survey. 2025

论文链接:https://arxiv.org/pdf/2504.08438

Dexterous Manipulation through Imitation Learning: A Survey.2025

论文链接:https://arxiv.org/pdf/2504.03515

Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision.2025

论文链接:https://arxiv.org/pdf/2504.02477

项目链接:https://github.com/Xiaofeng-Han-Res/MF-RV

SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey.2025

论文链接:https://arxiv.org/pdf/2503.09829

Generative Artificial Intelligence in Robotic Manipulation: A Survey.2025

论文链接:https://arxiv.org/pdf/2503.03464

项目链接:https://github.com/GAI4Manipulation/AwesomeGAIManipulation

Development Report of Embodied Intelligence (Chinese) .2025

论文链接:https://www.caict.ac.cn/kxyj/qwfb/bps/202408/P020240830312499650772.pdf

Survey on Vision-Language-Action Models.2025

论文链接:https://arxiv.org/pdf/2502.06851

Exploring Embodied Multimodal Large Models: Development, Datasets, and Future Directions.2025

论文链接:https://arxiv.org/pdf/2502.15336

Embodied-AI with large models: research and challenges.2025

论文链接:https://www.sciengine.com/SSI/doi/10.1360/SSI-2024-0076

A Survey on Vision-Language-Action Models for Embodied AI. 2024

论文链接:https://arxiv.org/abs/2405.14093

A Survey of Embodied Learning for Object-Centric Robotic Manipulation.2024

论文链接:https://arxiv.org/pdf/2408.11537

Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI.2024

论文链接:https://arxiv.org/pdf/2407.06886

Vision-language navigation: a survey and taxonomy.2024

论文链接:https://arxiv.org/pdf/2108.11544

All Robots in One: A New Standard and Unified Dataset for Versatile, General-Purpose Embodied Agents.2024

论文链接:https://arxiv.org/abs/2408.10899

Towards Generalist Robot Learning from Internet Video.2024

论文链接:https://arxiv.org/abs/2404.19664

Teleoperation of Humanoid Robots.2024

论文链接:https://arxiv.org/abs/2301.04317

A Survey on Robotics with Foundation Models: toward Embodied AI.2024

论文链接:https://arxiv.org/abs/2402.02385

如果您希望学习近30+具身路线,和近200家具身公司与机构成员交流,欢迎加入我们的知识星球!

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值