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https://github.com/GUOkekkk/awesome_AGI4Robotics

Some documents/code/paper/software for the AGI on Robotics
https://github.com/GUOkekkk/awesome_AGI4Robotics

List: awesome_AGI4Robotics

artificial-intelligence robotics

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Some documents/code/paper/software for the AGI on Robotics

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# awesome_AGI4Robotics [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

I think that, in a way, AGI(Artificial General Intelligence) will be the future of AI, and when it comes to robotics it is inseparable from AI, so this repository was created to document some of the research and applications of AGI in robotics. I will try to keep up with the cutting edge research and make a summary. It is mainly for myself as a personal study  repository.



## AGI(Artificial General Intelligence)

[AGI](https://en.wikipedia.org/wiki/Artificial_general_intelligence#) is also called strong AI, full AI, or general intelligent action, although some academic sources reserve the term "strong AI" for computer programs that experience sentience or consciousness. Strong AI contrasts with weak AI (or narrow AI), which is not intended to have general cognitive abilities but is designed to solve exactly one problem. 



#### Intelligence traits

There is wide agreement among artificial intelligence researchers that intelligence is required to do the following:

- reason, use strategy, solve puzzles, and make judgments under uncertainty;

- represent knowledge, including common sense knowledge;

- plan;

- learn;

-communicate in natural language;

and, if necessary, integrate all these skills in completion of any given goal. Other important capabilities include:

- input as the ability to sense (e.g. see, hear, etc.), and

- output as the ability to act (e.g. move and manipulate objects, change location to explore, etc.)

in environments where the above are possible. This includes the ability to detect and respond to hazard. Many interdisciplinary approaches to intelligence (e.g. cognitive science, computational intelligence, and decision making) consider additional traits such as imagination (taken as the ability to form mental images and concepts that were not programmed in) and autonomy.



## Common AGI Model

#### GPT

- [chatGPT](https://openai.com/blog/chatgpt)

- [GPT](https://s3-us-west-2.amazonaws.com/openai-assets/research-covers/language-unsupervised/language_understanding_paper.pdf)

- [GPT4](https://cdn.openai.com/papers/gpt-4.pdf)

- [AutoGPT](https://github.com/Significant-Gravitas/Auto-GPT)



#### Segment Anything

- [demo](https://segment-anything.com/)

- [paper](https://arxiv.org/pdf/2304.02643.pdf)

- [SAM + Stable Diffusion] ?

- [SAM + CLIP] ?

- [SAM-Adapter](https://tianrun-chen.github.io/SAM-Adaptor/static/pdfs/Adaptor.pdf)



#### DINOv2

- [demo](https://dinov2.metademolab.com/)

- [paper](https://arxiv.org/pdf/2304.07193.pdf)



#### ImageBind

- [demo](https://imagebind.metademolab.com/demo)

- [paper](https://arxiv.org/abs/2305.05665)



## AGI and Robot

#### [Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?](https://scontent-cdg4-2.xx.fbcdn.net/v/t39.2365-6/10000000_588381373355765_6700032118142617342_n.pdf?_nc_cat=109&ccb=1-7&_nc_sid=3c67a6&_nc_ohc=YF3hjxn-xv4AX_99jqJ&_nc_ht=scontent-cdg4-2.xx&oh=00_AfAta1TUSMvPrJUWWdefFaVm69hZBbzFCAF9-11tkFlgog&oe=644194EE) 



#### [Robots that learn from videos of human activities and simulated interactions](https://ai.facebook.com/blog/robots-learning-video-simulation-artificial-visual-cortex-vc-1/)



#### [Adaptive Skill Coordination for Robotic Mobile Manipulation](https://ai.facebook.com/research/publications/adaptive-skill-coordination-for-robotic-mobile-manipulation/)



#### [Lossless Adaptation of Pretrained Vision Models for Robotic Manipulation](https://sites.google.com/view/robo-adapters)



#### [ChatGPT for Robotics: Design Principles and Model Abilities](https://www.microsoft.com/en-us/research/uploads/prod/2023/02/ChatGPT___Robotics.pdf)



#### [Unifying learning from preferences and demonstration via a ranking game for imitation learning](https://www.microsoft.com/en-us/research/blog/unifying-learning-from-preferences-and-demonstration-via-a-ranking-game-for-imitation-learning/)



#### [Deep Reinforcement Learning on Soccer](https://sites.google.com/view/op3-soccer/home?authuser=0)



#### [Deep Reinforcement Learning on Walk(Unity+ML-Agents)](https://www.youtube.com/watch?v=L_4BPjLBF4E)



#### [ROSGPT](https://github.com/aniskoubaa/rosgpt/)



#### [RLBench](https://github.com/stepjam/RLBench)



#### [RT-1: Robotics Transformer](https://robotics-transformer.github.io/)



#### [Embodied AI](https://medium.com/machinevision/overview-of-embodied-artificial-intelligence-b7f19d18022)

For me, the Embodied AI is more like the robot&AI but in a simulation platform.



#### [RoboAgent](https://robopen.github.io/?utm_source=linkedin&utm_medium=organic_social&utm_campaign=research&utm_content=video)



## Robot Simulation Platform

#### [Mujoco_wasm](https://github.com/zalo/mujoco_wasm)

#### [Pybullet](https://pybullet.org/wordpress/)

#### [Mujoco_menagerie](https://github.com/deepmind/mujoco_menagerie)

#### [Dynamic Environment](https://github.com/eliabntt/GRADE-RR/)

#### [CoppeliaSim](https://www.coppeliarobotics.com/)

#### [Nvidia ISAAC](https://developer.nvidia.cn/isaac)



## Sim2Real

#### [Basic](https://zhuanlan.zhihu.com/p/510951914)

#### [IndoorSim-to-OutdoorReal](https://www.joannetruong.com/projects/i2o.html)

#### [Rethinking Sim2Real: Lower Fidelity Simulation Leads to Higher Sim2Real Transfer in Navigation](http://www.joannetruong.com/projects/kin2dyn.html)



## Dateset

#### [CortexBench](https://github.com/facebookresearch/eai-vc/blob/main/cortexbench/DATASETS.md)



## Hardware Support

#### [NVIDIA Isaac ROS](https://developer.nvidia.com/blog/build-high-performance-robotic-applications-with-nvidia-isaac-ros-developer-preview-3/)



## Software Support

#### [OpenAI Gym](https://www.analyticsvidhya.com/blog/2019/04/introduction-deep-q-learning-python/)

#### [Pypose: PyTorch-based robotics-oriented coonecting deep learning with physics-based optimization](https://sairlab.org/pypose/)

#### [Flowstate](https://intrinsic.ai/)