Best AI tools for< Research Robotics >

Duckietown is a platform for delivering cutting-edge robotics and AI learning experiences. It offers teaching resources to instructors, hands-on activities to learners, an accessible research platform to researchers, and a state-of-the-art ecosystem for professional training. Duckietown's mission is to make robotics and AI education state-of-the-art, hands-on, and accessible to all.

The Berkeley Artificial Intelligence Research (BAIR) Lab is a renowned research lab at UC Berkeley focusing on computer vision, machine learning, natural language processing, planning, control, and robotics. With over 50 faculty members and 300 graduate students, BAIR conducts research on fundamental advances in AI and interdisciplinary themes like multi-modal deep learning and human-compatible AI.

Dobb·E is an open-source, general framework for learning household robotic manipulation. It aims to create a 'generalist machine' for homes that can adapt and learn various tasks cost-effectively. Dobb·E can learn a new task in just five minutes of demonstration, thanks to a tool called 'The Stick' for data collection. The system achieved an 81% success rate in completing 109 tasks across 10 homes in New York City. Dobb·E is designed to accelerate research on home robots and make robot assistants a common sight in households.

Hanson Robotics is an AI and robotics company dedicated to creating socially intelligent machines that enrich the quality of our lives. The company's team of renowned AI scientists conducts advanced research to build the most compelling robotics and AI platform for research, media, and service applications.

Aiiot Talk is an AI tool that focuses on Artificial Intelligence, Robotics, Technology, Internet of Things, Machine Learning, Business Technology, Data Security, and Marketing. The platform provides insights, articles, and discussions on the latest trends and applications of AI in various industries. Users can explore how AI is reshaping businesses, enhancing security measures, and revolutionizing technology. Aiiot Talk aims to educate and inform readers about the potential of AI and its impact on society and the future.

Amazon Science is a research and development organization within Amazon that focuses on developing new technologies and products in the fields of artificial intelligence, machine learning, and computer science. The organization is home to a team of world-renowned scientists and engineers who are working on a wide range of projects, including developing new algorithms for machine learning, building new computer vision systems, and creating new natural language processing tools. Amazon Science is also responsible for developing new products and services that use these technologies, such as the Amazon Echo and the Amazon Fire TV.

Artificial Intelligence + is a comprehensive platform focusing on AI, Robotics, and IoT. It covers a wide range of topics related to artificial intelligence, including the dangers, impacts, and advancements in the field. The platform also delves into robotics, space exploration, and the intersection of AI with various industries. With a mix of articles, blogs, and expert insights, Artificial Intelligence + serves as a valuable resource for individuals interested in staying updated on the latest trends and developments in the AI landscape.

FOXSY.AI is an AI application that combines robotics and AI to create fully autonomous humanoid robot soccer players. The project aims to achieve the RoboCup final goal of having a team of robots win a soccer game against the winner of the most recent World Cup. The $FOXSY token powers the implementation of robotics and AI research, enabling users to engage with the RoboCup mechanics for entertainment value. The application offers various tools and features for users to participate in online tournaments, customize players, and analyze game strategies.

The website focuses on Robotics & A.I. Research and Development, providing information on various AI applications and technologies. It covers topics such as AI in healthcare, robotics, space technology, quantum computing, and more. The site also discusses the integration of AI in everyday devices like smartphones and explores the impact of AI on different industries. Additionally, it features articles on AI tools, career trends post-AI, AI in e-commerce, and the use of AI in companies like Amazon and Salesforce.

Mobility Engineering is a website that provides news, articles, and resources on the latest developments in mobility technology. The site covers a wide range of topics, including autonomous vehicles, connected cars, electric vehicles, and more. Mobility Engineering is a valuable resource for anyone interested in staying up-to-date on the latest trends in mobility technology.

NORA (Norwegian Artificial Intelligence Research Consortium) is a collaborative platform between 8 universities, 5 university colleges, and 5 research institutes in Norway focusing on AI, machine learning, and robotics. The consortium aims to enhance research, education, and innovation in these fields, fostering a vibrant community of researchers, educators, and innovators.

Engadget is a leading technology news and reviews website that covers the latest gadgets, apps, and trends. It offers in-depth reviews of the latest smartphones, laptops, TVs, and other consumer electronics, as well as news and analysis on the latest developments in the tech industry. Engadget also has a strong focus on AI and robotics, with dedicated sections covering the latest advancements in these fields.

AI News is a website dedicated to providing news, analysis, and insights related to artificial intelligence (AI) technologies. The site covers a wide range of topics within the AI domain, including applications, chatbots, face recognition, virtual assistants, voice recognition, companies like Amazon, Apple, Google, and Microsoft, as well as deep learning, ethics, industries, machine learning, robotics, security, and more. AI News aims to keep readers informed about the latest developments, trends, and innovations in the field of artificial intelligence.

Nuro is an autonomous technology company focused on revolutionizing mobility through robotics and AI. They offer cutting-edge AI-first autonomy solutions for automotive and mobility applications, including robotaxis and autonomous vehicles. Nuro's state-of-the-art AV technology, Nuro Driver™, is designed to drive safely and naturally on all roads using groundbreaking AI-first autonomy. The company prioritizes safety in all aspects of its operations, from hardware and software to testing and systems engineering. With 8 years of autonomy innovation, Nuro aims to transform the way goods and people move by empowering fleets with AI-first autonomous capabilities.

CogPrints is an electronic archive for self-archived papers in any area of Psychology, Neuroscience, and Linguistics, and many areas of Computer Science (e.g., artificial intelligence, robotics, vision, learning, speech, neural networks), Philosophy (e.g., mind, language, knowledge, science, logic), Biology (e.g., ethology, behavioral ecology, sociobiology, behavior genetics, evolutionary theory), Medicine (e.g., Psychiatry, Neurology, human genetics, Imaging), Anthropology (e.g., primatology, cognitive ethnology, archeology, paleontology), as well as any other portions of the physical, social and mathematical sciences that are pertinent to the study of cognition.

Stanford HAI is a research institute at Stanford University dedicated to advancing AI research, education, and policy to improve the human condition. The institute brings together researchers from a variety of disciplines to work on a wide range of AI-related projects, including developing new AI algorithms, studying the ethical and societal implications of AI, and creating educational programs to train the next generation of AI leaders. Stanford HAI is committed to developing human-centered AI technologies and applications that benefit all of humanity.

Adept is building a machine learning model that can interact with everything on your computer. It takes your goals, in plain language, and turns them into actions on the software you use every day. Adept is designed and trained specifically for taking actions on computers in response to your natural language commands. ACT-1 is Adept's first step towards a foundation model that can use every software tool, API, and website that exists.

The NVIDIA Toronto AI Lab is a research laboratory focused on advancing the state-of-the-art in artificial intelligence. The lab's researchers are working on a wide range of AI topics, including deep learning, machine learning, computer vision, natural language processing, and robotics.

GenInnov is a generative innovation fund that provides a platform for investors seeking to be at the forefront of technological advancement. The fund invests in companies driving transformative change across multiple sectors and geographies, prioritizing material innovations with demonstrable profitability and global reach. GenInnov operates with a research-driven approach, focusing on investing in material innovations that are monetizable, profitable, and transformative, rather than incremental. The fund looks at various domains such as technology, robotics, consumer electronics, biotech, healthcare, mobility, and clean tech, aiming to amplify human creativity through machine intelligence.

TensorFlow is an end-to-end platform for machine learning. It provides a wide range of tools and resources to help developers build, train, and deploy ML models. TensorFlow is used by researchers and developers all over the world to solve real-world problems in a variety of domains, including computer vision, natural language processing, and robotics.

The Everything-LLMs-And-Robotics repository is the world's largest GitHub repository focusing on the intersection of Large Language Models (LLMs) and Robotics. It provides educational resources, research papers, project demos, and Twitter threads related to LLMs, Robotics, and their combination. The repository covers topics such as reasoning, planning, manipulation, instructions and navigation, simulation frameworks, perception, and more, showcasing the latest advancements in the field.

This repository contains a curated list of **papers using Large Language/Multi-Modal Models for Robotics/RL**. Template from awesome-Implicit-NeRF-Robotics Please feel free to send me pull requests or email to add papers! If you find this repository useful, please consider citing and STARing this list. Feel free to share this list with others! ## Overview * Surveys * Reasoning * Planning * Manipulation * Instructions and Navigation * Simulation Frameworks * Citation

The 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.

The neo is an open source robotics research platform powered by a OnePlus 3 smartphone and an STM32F205-based CAN interface board, housed in a 3d-printed casing with active cooling. It includes NEOS, a stripped down Android ROM, and offers a modern Linux environment for development. The platform leverages the high performance embedded processor and sensor capabilities of modern smartphones at a low cost. A detailed guide is available for easy construction, requiring online shopping and soldering skills. The total cost for building a neo is approximately $700.

OpenCat is an open-source Arduino and Raspberry Pi-based quadruped robotic pet framework developed by Petoi. It aims to foster collaboration in quadruped robotics research, education, and engineering development of agile and affordable quadruped robot pets. The project provides a base open source platform for creating programmable gaits, locomotion, and deployment of inverse kinematics quadruped robots, enabling simulations to the real world via block-based coding/C/C++/Python programming languages. Users have deployed various robotics/AI/IoT applications and the project has successfully crowdfunded mini robot kits, shipped worldwide, and established a production line for affordable robotic kits and accessories.

ROSA is an AI Agent designed to interact with ROS-based robotics systems using natural language queries. It can generate system reports, read and parse ROS log files, adapt to new robots, and run various ROS commands using natural language. The tool is versatile for robotics research and development, providing an easy way to interact with robots and the ROS environment.

LeRobot is a state-of-the-art AI library for real-world robotics in PyTorch. It aims to provide models, datasets, and tools to lower the barrier to entry to robotics, focusing on imitation learning and reinforcement learning. LeRobot offers pretrained models, datasets with human-collected demonstrations, and simulation environments. It plans to support real-world robotics on affordable and capable robots. The library hosts pretrained models and datasets on the Hugging Face community page.

Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.

Awesome-Robotics-3D is a curated list of 3D Vision papers related to Robotics domain, focusing on large models like LLMs/VLMs. It includes papers on Policy Learning, Pretraining, VLM and LLM, Representations, and Simulations, Datasets, and Benchmarks. The repository is maintained by Zubair Irshad and welcomes contributions and suggestions for adding papers. It serves as a valuable resource for researchers and practitioners in the field of Robotics and Computer Vision.

AimRT is a basic runtime framework for modern robotics, developed in modern C++ with lightweight and easy deployment. It integrates research and development for robot applications in various deployment scenarios, providing debugging tools and observability support. AimRT offers a plug-in development interface compatible with ROS2, HTTP, Grpc, and other ecosystems for progressive system upgrades.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

This repository is a curated list of papers related to 3D tasks empowered by Large Language Models (LLMs). It covers tasks such as 3D understanding, reasoning, generation, and embodied agents. The repository also includes other Foundation Models like CLIP and SAM to provide a comprehensive view of the area. It is actively maintained and updated to showcase the latest advances in the field. Users can find a variety of research papers and projects related to 3D tasks and LLMs in this repository.

This repository, named Awesome-Embodied-Agent-with-LLMs, is a curated list of research related to Embodied AI or agents with Large Language Models. It includes various papers, surveys, and projects focusing on topics such as self-evolving agents, advanced agent applications, LLMs with RL or world models, planning and manipulation, multi-agent learning and coordination, vision and language navigation, detection, 3D grounding, interactive embodied learning, rearrangement, benchmarks, simulators, and more. The repository provides a comprehensive collection of resources for individuals interested in exploring the intersection of embodied agents and large language models.

GOLEM is an open-source AI framework focused on optimization and learning of structured graph-based models using meta-heuristic methods. It emphasizes the potential of meta-heuristics in complex problem spaces where gradient-based methods are not suitable, and the importance of structured models in various problem domains. The framework offers features like structured model optimization, metaheuristic methods, multi-objective optimization, constrained optimization, extensibility, interpretability, and reproducibility. It can be applied to optimization problems represented as directed graphs with defined fitness functions. GOLEM has applications in areas like AutoML, Bayesian network structure search, differential equation discovery, geometric design, and neural architecture search. The project structure includes packages for core functionalities, adapters, graph representation, optimizers, genetic algorithms, utilities, serialization, visualization, examples, and testing. Contributions are welcome, and the project is supported by ITMO University's Research Center Strong Artificial Intelligence in Industry.

Korea-Startups is a repository containing a comprehensive list of major tech companies and startups in Korea. It covers a wide range of industries such as mobility, local community trading, food tech, interior design, fintech, AI, natural language processing, computer vision, robotics, legal tech, and more. The repository provides detailed information about each company's field, key services, and unique features, showcasing the diverse and innovative startup ecosystem in Korea.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

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