# Robotics An interdisciplinary field concerned with designing, constructing, operating, and using programmable machines that perform physical tasks, integrating computer science with engineering and control theory. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How to Use AI Agents to Prepare 3D Scenes for Simulation DevFeed: [How to Use AI Agents to Prepare 3D Scenes for Simulation]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-09-16T23:20:33Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Artificial Intelligence](), [Simulation](), [Physical AI](), [Simulation and Design](), [blender](), [Isaac Sim](), [Omniverse](), [Robotics Simulation](), [Robotics]() Tags: [3d](), [agentic](), [agentic-ai-generative-ai](), [agents](), [ai](), [blender](), [gpt-6-astra](), [how-to](), [isaac-sim](), [nemoclaw](), [nvidia](), [omniverse](), [openai](), [openusd](), [physical-ai](), [robotics](), [robotics-simulation](), [simulation](), [simulation-modeling-design]() ### AI overview This tutorial describes an agentic workflow for preparing Blender 3D scenes for robotics simulation. It covers scene inspection, OpenUSD metadata, physics properties, rendering preflight views, and validation for simulation-ready handoff to NVIDIA Isaac Sim or Isaac Lab. ### Source excerpt Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in... ## MYWAI ports its VILMA visual imitation learning toolkit to Arduino UNO Q and VENTUNO Q DevFeed: [MYWAI ports its VILMA visual imitation learning toolkit to Arduino UNO Q and VENTUNO Q]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-15T14:26:17Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [Robotics](), [Artificial Intelligence](), [Computer vision](), [Arduino](), [Qualcomm](), [UNO Q](), [VENTUNO Q]() Tags: [ai](), [arduino](), [computer-vision](), [edge-ai](), [industrial](), [machine-learning](), [qualcomm](), [robotics](), [robots](), [uno-q](), [ventuno-q](), [warehouse]() ### AI overview The article describes VILMA, an AI-powered toolkit from MYWAI that enables robots and humanoids to learn manipulation tasks from one-shot human demonstrations. It reports that the toolkit is being ported to Arduino UNO Q and VENTUNO Q boards powered by Qualcomm Dragonwing processors. ### Source excerpt Every day, hundreds of thousands of kits are prepared in warehouses before components ever reach an automotive production line. While robots have become commonplace in modern manufacturing, many upstream logistics activities still rely heavily on human operators performing repetitive pick-and-place and kitting tasks. What if robots could learn these operations the same way humans do: [...] The post MYWAI™ VILMA™ is designed to bring human-like learning to robots via one-shot demonstration appeared first on Arduino Blog. ## Supporter spotlight: Jochen Sprickerhof on reproducible builds DevFeed: [Supporter spotlight: Jochen Sprickerhof on reproducible builds]() Original publisher: [Read original article]() Published: 2026-09-15T03:54:00Z Content type: news Language: en Sources: [reproducible-builds.org]() Topics: [reproducible builds](), [Open Source](), [Debian](), [Programming](), [F-Droid](), [Robotics](), [Point cloud]() Tags: [debian](), [open-source](), [org](), [programming](), [reproducible-builds](), [robotics]() ### AI overview An interview with Jochen Sprickerhof, a freelance programmer and Reproducible Builds core team member, covering his work on Debian, F-Droid, software projects, and bit-for-bit reproduction of Debian packages. ### Source excerpt The Reproducible Builds project relies on several projects, supporters and sponsors for financial support, but they are also valued as ambassadors who spread the word about our project and the work that we do. This is the ninth installment in a series featuring the projects, companies and individuals who support the Reproducible Builds project. We started this series by featuring the Civil Infrastructure Platform project, and followed this up with a post about the Ford Foundation as well as recent ones about ARDC, the Google Open Source Security Team (GOSST), Bootstrappable Builds, the F-Droid project, David A. Wheeler, Simon Butler and Kees Cook. Today, however, we will be talking with Jochen Sprickerhof, one of the newer members of the Reproducible Builds project core team. Vagrant Cascadian: Could you tell me a bit about yourself? What sort of things do you work on? Jochen Sprickerhof: I am a freelance programmer working on Open Source. Mainly doing Debian, F-Droid and some smaller software projects. In general I made it a habit to look into every software I use and try to fix bugs or add features I need. In Debian, I maintain about 180 packages with topics covering home banking, build systems and robotics. Most of my time, I currently work on reproduce.debian.net, where we try to bit-for-bit reproduce the packages distributed by Debian. Vagrant: Could you describe the path that lead you to working on reproducible builds? Jochen: I started my Debian journey as a teenager, converting my school to Debian and serving as its system administrator for 13 years. After studying Applied System Science, I joined the university's robotics labs, where I worked on the Robot Operating System (ROS) and the Point Cloud Library (PCL). In the end, I enjoyed programming more than writing papers, so I eventually left academia for a robotics startup. Some years ago, I realized that the open source work I was doing in my spare time was actually the work I cared most about. Nowadays I ## How BitRobot Crowdsources Real-World Data for Embodied AI, with Jonathan Victor DevFeed: [How BitRobot Crowdsources Real-World Data for Embodied AI, with Jonathan Victor]() Original publisher: [Read original article]() Author: Amira Valliani Published: 2026-09-07T07:00:00Z Content type: article Language: en Sources: [Solana News Feed]() Topics: [datasets](), [Robotics](), [Robot Navigation](), [Solana](), [Artificial Intelligence]() Tags: [ai](), [blockchain](), [blockchain-technology](), [crypto-news](), [cryptocurrency](), [dataset](), [defi](), [depin](), [nfts](), [payments](), [podcasts](), [robot-navigation](), [robotics](), [solana](), [solana-ecosystem](), [training](), [web3]() ### AI overview The article discusses how BitRobot crowdsources real-world interaction data for embodied AI. It describes FrodoBots, which generated roughly 2,000 hours of urban robot navigation data, and explains how BitRobot uses a network model to produce and reward contributors of robotics data. ### Source excerpt BitRobot open-sourced 2,000 hours of robot navigation data and uses Solana to track and reward embodied AI data contributors. ## Petoi Quaddle - A mini robot dog for physical AI experimentation (Crowdfunding) DevFeed: [Petoi Quaddle - A mini robot dog for physical AI experimentation (Crowdfunding)]() Original publisher: [Read original article]() Author: Jean-Luc Aufranc (CNXSoft) Published: 2026-09-04T08:03:49Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Robotics](), [Physical AI](), [ESP32-S3](), [Arduino](), [Raspberry Pi](), [coding](), [Open Source]() Tags: [3d-printing](), [arduino](), [broadcom-bcmxxxx](), [c-c-plus-plus](), [crowdfunding](), [edge-ai](), [education](), [esp32](), [esp32-s3](), [esphome](), [espressif](), [hardware](), [micropython](), [open-source](), [physical-ai](), [raspberry-pi](), [robot-dog](), [robotics](), [ros](), [simulator](), [smart-home](), [smart-speaker](), [stem](), [video]() ### AI overview The Petoi Quaddle is a mini robot dog designed for learning robotics, coding, physical AI, and 3D printing. It uses an ESP32-S3 motion core, optional AI hardware, OpenCat firmware, and multiple programming environments. Petoi launched it on Kickstarter with three models and planned December 2026 shipping. ### Source excerpt If you are not into ducks, but still would like to play around with physical AI, the Petoi Quaddle is a mini robot dog equipped with 4 servos controlling its legs and is designed to help people learn robotics, coding, AI, and 3D printing. The robot is powered by an ESP32-S3 motion core for servo control and wireless connectivity, and an optional ESP32-S3 AI core to enable voice commands and Smart Home control. The robot can walk, strafe, spin, talk back, and react to the user's touch. Three models are available depending on the user's requirements: Builder, Buddy, and Scout. A Raspberry Pi Zero can also be mounted on the top in place of the ESP32-S3-based AI core. Petoi Quaddle runs OpenCat open-source firmware (Arduino) already used in the earlier Petoi Bittle robot dog, first introduced in 2020. The robot can be programmed in a visual programming IDE with drag-and-drop [...] The post Petoi Quaddle - A mini robot dog for physical AI experimentation (Crowdfunding) appeared first on CNX Software - Embedded Systems News. ## Arduino Core on Zephyr 1.0.0 is here! DevFeed: [Arduino Core on Zephyr 1.0.0 is here!]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-03T15:20:44Z Content type: release Language: en Sources: [Arduino Blog]() Topics: [Arduino](), [Release notes](), [Hardware](), [real-time](), [Robotics](), [Automation](), [Qualcomm]() Tags: [arduino](), [arduino-core-on-zephyr](), [arduino-ide](), [bug-fixes](), [camera](), [image-classification](), [object-detection](), [physical-ai](), [qualcomm](), [real-time](), [release](), [robotics](), [ventuno-q](), [zephyr]() ### AI overview Arduino announced ArduinoCore-Zephyr 1.0.0, adding support for the VENTUNO Q board, updating the base to Zephyr 4.4.1, enabling camera support for the Nicla Vision module, and including bug fixes and cleanup. ### Source excerpt We're excited to announce version 1.0.0 of the ArduinoCore-Zephyr, our biggest release yet. Building on the stability milestone we hit with 0.90.0, this release brings new hardware support, an updated Zephyr base, and a long list of fixes and improvements across the core. Thank you to everyone who tested 0.90.0, filed issues, and helped us [...] The post Arduino Core on Zephyr 1.0.0 is here! appeared first on Arduino Blog. ## System helps humans predict when self-driving cars will make mistakes DevFeed: [System helps humans predict when self-driving cars will make mistakes]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-09-02T15:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [autonomous vehicles](), [Deep learning](), [Artificial Intelligence](), [Robotics](), [Simulation](), [Computer science]() Tags: [aeronautical-and-astronautical-engineering](), [ai](), [artificial-intelligence](), [autonomous-vehicles](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [concept-wrapper-network](), [cw-net](), [deep](), [electrical-engineering-and-computer-science-eecs](), [eoin-kenny](), [human-computer-interaction](), [julie-shah](), [laura-major](), [machine-learning](), [mit-schwarzman-college-of-computing](), [momchil-tomov](), [motional](), [research](), [robotics](), [safety](), [school-of-engineering](), [self-driving](), [self-driving-cars](), [simulation](), [transparency]() ### AI overview MIT and Motional researchers developed CW-Net, a method that translates an autonomous vehicle's deep-learning decisions into understandable concepts. Tests found that the explanations helped safety drivers and nonexpert users better predict vehicle behavior. ### Source excerpt A new method, called CW-Net, translates the reasoning process of an autonomous vehicle's AI system into understandable concepts that explain its behavior. ## D-Robotics RDK S100P - A 128 TOPS alternative to NVIDIA Jetson Orin NX 16GB with Cortex-A78AE/R52+ cores DevFeed: [D-Robotics RDK S100P - A 128 TOPS alternative to NVIDIA Jetson Orin NX 16GB with Cortex-A78AE/R52+ cores]() Original publisher: [Read original article]() Author: Debashis Das Published: 2026-08-31T08:06:13Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Jetson](), [Robotics](), [Embedded Systems](), [Microcontroller](), [Jetson Orin](), [SOC](), [cpu](), [Arm](), [real-time](), [GPU](), [Linux](), [Nvidia]() Tags: [arm](), [artificial-intelligence-ai](), [camera](), [computer-vision](), [cortex-a78](), [cpu](), [deep-learning](), [development-kit](), [dfrobot](), [edge-ai](), [embedded](), [embedded-systems](), [gpu](), [hardware](), [jetson](), [jetson-orin](), [linux](), [mcu](), [networking](), [nvidia](), [os](), [processors](), [real-time](), [robotics](), [ros](), [safety](), [sensor](), [sensors](), [single-board-computer](), [soc](), [software](), [som](), [specifications](), [systems](), [ubuntu]() ### AI overview The D-Robotics RDK S100P is a robotics single-board computer featuring a 6-core Cortex-A78AE CPU, 4-core Cortex-R52+ MCU domain, 128 TOPS INT8 Nash BPU, Mali-G78AE GPU, and 24 GB of LPDDR5. Its MCU supports real-time motor and sensor control, potentially reducing the need for a separate real-time controller depending on the robot's requirements. ### Source excerpt D-Robotics RDK S100P development kit is a robotics SBC built around an S100P-based module providing an alternative to NVIDIA Jetson Orin NX 16GB with a 6-core Cortex-A78AE application cluster, a 4-core Cortex-R52+ MCU domain, a Nash BPU rated at 128 TOPS INT8, a Mali-G78AE GPU, and 24 GB of LPDDR5. The four R52+ cores can be configured for reliable real-time control: two cores run in lockstep for safety, and the other two support split-lock operation. In practice, the A78AE CPU and BPU can handle Linux and vision processing, while the MCU handles time-critical tasks such as motor and sensor I/O. This can reduce the need for a separate real-time controller, although whether it eliminates one depends on the robot and its requirements. RDK S100P specifications: SoC - D-Robotics S100P CPU - 6x Arm Cortex-A78AE @ 2.0 GHz (safety-capable AE cores) MCU - 4x Arm Cortex-R52+ @ 1.2 GHz (1x DCLS [...] The post D-Robotics RDK S100P - A 128 TOPS alternative to NVIDIA Jetson Orin NX 16GB with Cortex-A78AE/R52+ cores appeared first on CNX Software - Embedded Systems News. ## Sergey Levine: Current State of Humanoid Robotics, China & Future Predictions DevFeed: [Sergey Levine: Current State of Humanoid Robotics, China & Future Predictions]() Original publisher: [Read original article]() Author: Ryan Peterman Published: 2026-08-24T13:05:33Z Content type: opinion Language: en Sources: [The Developing Dev]() Topics: [Robotics](), [Humanoid Robots](), [Physical AI](), [Machine learning](), [Large Language Model]() Tags: [china](), [future](), [humanoid-robots](), [llms](), [machine-learning](), [physical-ai](), [predictions](), [robotics]() ### AI overview An interview with robotics researcher Sergey Levine examines the current state of humanoid robotics, China's robotics ecosystem, possible competitors, future timelines, and how humanoid robots may be deployed. Levine discusses the importance of scaling the right technology, data, and model size. ### Source excerpt Sergey Levine is one of the world's top robotics researchers and co-founder of Physical Intelligence. ## GeoPT helps AI models simulate how objects respond to physical forces DevFeed: [GeoPT helps AI models simulate how objects respond to physical forces]() Original publisher: [Read original article]() Author: Alex Shipps | MIT CSAIL Published: 2026-08-10T19:25:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [AI Models](), [Simulation](), [AI Research](), [Computer Science and Artificial Intelligence Laboratory (CSAIL)](), [Robotics]() Tags: [3-d-imaging](), [ai](), [ai-models](), [artificial-intelligence](), [computational-fluid-dynamics-cfd](), [computer-graphics](), [computer-modeling](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [crash-simulation](), [design](), [electrical-engineering-and-computer-science-eecs](), [geometric-pre-training](), [geopt](), [haixu-wu](), [human-computer-interaction](), [kaiming-he](), [manufacturing](), [minghao-guo](), [mit-csail](), [mit-eecs](), [mit-schwarzman-college-of-computing](), [neural-physics-simulation](), [paper](), [physics](), [physics-aware-ai](), [physics-foundation-models](), [research](), [robotics](), [school-of-engineering](), [self-supervised-learning](), [simulation](), [surrogate-modeling](), [synthetic-dynamics](), [transformer-based-simulators](), [wojciech-matusik]() ### AI overview Researchers at MIT CSAIL and Tsinghua University developed GeoPT, a pre-training approach that uses 3D simulations of mechanical interactions to help AI models learn physics more efficiently. The article reports that models using the approach reached peak performance twice as fast and trained on up to 60 percent less data than leading models. ### Source excerpt "GeoPT" helps AI models understand the basics of physics so they can simulate how objects respond to things like wind and water more efficiently and accurately. ## Waggy, Claude, and Code: Celebrating Drake Fish, Our Newest Beacon DevFeed: [Waggy, Claude, and Code: Celebrating Drake Fish, Our Newest Beacon]() Original publisher: [Read original article]() Author: Juan Santana Published: 2026-08-10T05:00:00Z Content type: opinion Language: en Sources: [8th Light](), [8th Light Insights]() Topics: [Artificial Intelligence](), [Claude](), [anthropic](), [Robotics](), [Code](), [Slack]() Tags: [ai](), [anthropic](), [claude](), [culture-and-news](), [robotics](), [slack](), [work]() ### AI overview An 8th Light profile celebrates Drake Fish as a Beacon Award recipient, highlighting his open sharing of the Waggy autonomous robot project, experimentation with Claude and real-world hardware, and work helping colleagues and clients adopt AI systems. ### Source excerpt Working at 8th Light, we have the daily privilege of collaborating with truly brilliant minds--people who bridge the gap between deep engineering and meaningful human connection. We are also incredibly fortunate to work alongside folks who, no matter how tough the problem or early the hour, are overflowing with honesty, curiosity, and of course, the jokes. That's why it brings us immense joy to announce our latest Beacon Award recipient at 8th Light, Drake Fish! The Beacon Award is a peer-nominated honor celebrating the individuals who bring 8th Light's values to life and elevate everyone around them. Drake was nominated by multiple colleagues last quarter, which tells you everything you need to know about his impact. As a Lead Engineer, Drake has built a reputation at 8th Light that reaches far beyond client teams. The secret sauce? He learns in the open, bringing everyone along for the ride. Waggy is an autonomous robot pooper scooper that Drake started building in his spare time. He stepped into the project without much background in electronics or robotics. Instead of tinkering quietly in private until everything worked, Drake shared the entire journey in Slack (mistakes, wiring mishaps, and all) so the rest of the company could learn, and giggle, alongside him. Along the way, Drake used Waggy to give us a front-row seat to what agentic tools like Claude can actually accomplish when paired with real-world hardware and a little bit of experimentation. As if building an autonomous pooper scooper wasn't enough, Drake took his AI experimentation even further. He became the first of many 8th Light team members to earn the Claude Certified Architect credential, one of Anthropic's benchmarks for engineers building production-grade AI systems. Right after passing the exam, he presented to the company to share tips, break down the material, and demystify the process. If you drop into our internal AI Slack channels or our "AI in the Open" sessions, odds are high you will f ## How Physical Intelligence unified its robotics data stack with Postgres managed by ClickHouse DevFeed: [How Physical Intelligence unified its robotics data stack with Postgres managed by ClickHouse]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-08-06T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Robotics](), [foundation-models](), [data](), [Artificial Intelligence](), [Cloud]() Tags: [ai](), [clickhouse](), [data](), [foundation-models](), [model](), [research](), [robotics](), [robots]() ### AI overview Physical Intelligence describes how it uses ClickHouse Cloud and ClickHouse-managed Postgres to support robotics foundation-model research. The unified data stack combines analytical and transactional workloads, helping the company explore datasets that have grown to roughly 10-100 billion rows. ### Source excerpt Physical Intelligence runs both its OLAP and OLTP workloads on ClickHouse managed Postgres and ClickHouse Cloud ## Beyond VLAs: How World Action Models Reshape Robot Manipulation DevFeed: [Beyond VLAs: How World Action Models Reshape Robot Manipulation]() Original publisher: [Read original article]() Author: Michelle Horton Published: 2026-08-04T16:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Robotics](), [World models](), [vlm](), [post-training](), [Cosmos](), [Nvidia](), [NVIDIA Research]() Tags: [agentic-ai-generative-ai](), [cosmos](), [featured](), [nvidia](), [nvidia-research](), [physical-ai](), [post-training](), [robot-manipulation](), [robotics](), [simulation-modeling-design](), [thor](), [vlm](), [world-model](), [zero-shot]() ### AI overview The article explains how World Action Models (WAMs) use video world models as backbones for robot policies, addressing the physical-generalization limitations of vision-language-action models. It discusses post-training WAMs into specialized policies and presents NVIDIA Cosmos 3 as a foundation for building them. ### Source excerpt A central challenge in robotics is building policies that generalize beyond the demonstrations they're trained on. A policy that succeeds in a training scene... ## Чем запомнилась ICRA 2026: Reinforcement Learning, генерация сложных сценариев поведения и будущее робототехники DevFeed: [Чем запомнилась ICRA 2026: Reinforcement Learning, генерация сложных сценариев поведения и будущее робототехники]() Original publisher: [Read original article]() Author: egavolk (Яндекс) Published: 2026-08-04T08:00:45Z Content type: article Language: ru Sources: [Яндекс - Как мы делаем Яндекс / Статьи]() Topics: [Reinforcement learning](), [Robotics](), [Simulation](), [Machine learning]() Tags: [2026](), [icra](), [ml](), [reinforcement-learning](), [rl](), [robotics](), [simulation](), [tag-511fbf58fd45](), [tag-6faff4be08e9](), [tag-d704a344cc75](), [tag-dace475544fb]() ### AI overview The article reviews notable trends, papers, and engineering trade-offs discussed at ICRA 2026, with emphasis on reinforcement learning, autonomous-vehicle perception and planning pipelines, simulation, rare edge-case generation, and robotic learning. It also discusses award-winning work on manipulation, humanoid robots, and camera-conditioned policy learning. ### Source excerpt Привет, Хабр! В начале июня в Вене прошла главная международная конференция по робототехнике и автономным системам -- International Conference on Robotics and Automation (ICRA). В этом году среди участников была и наша команда автономного транспорта Яндекса. Топиков, которые обсуждаются на ICRA, много, потому что она не только об ML -- она скорее о робототехнике в целом. Например, есть секции о механизмах и дизайне, а также о медицинских роботах. Было немало и чисто инженерных работ. Ключевой топик докладов на конференции -- RL, он же Reinforcement Learning, обучение с подкреплением. Также нас интересовали статьи по классическому пайплайну автономного автомобиля: perception + prediction + planner + simulation. Новые подходы к Robotic Learning тоже интересны, так как их можно перенести на задачи автономного транспорта. Меня зовут Егор Волков, я занимаюсь претрейном модели планирования движения в автономном транспорте Яндекса. Вместе со мной на конференцию ездил Максим Спорышев -- руководитель службы поведения и предсказания движения. В этой статье мы собрали самые интересные тренды, доклады и инженерные развилки, которые заметили на ICRA 2026, -- от Reinforcement Learning и генерации редких edge-кейсов до того, куда вообще двигается ML в робототехнике. Читать далее ## Developing Healthcare Robotics with GPU-Native Medical Physics Simulation DevFeed: [Developing Healthcare Robotics with GPU-Native Medical Physics Simulation]() Original publisher: [Read original article]() Author: Michelle Horton Published: 2026-07-28T20:49:21Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Isaac for Healthcare](), [Robotics](), [Reinforcement learning](), [GPU](), [datasets](), [Medical imaging](), [Cosmos](), [Open Source](), [real-time](), [Nvidia]() Tags: [agentic-ai-generative-ai](), [data](), [datasets](), [featured](), [gpu](), [healthcare](), [isaac](), [isaac-for-healthcare](), [isaac-sim](), [medical-imaging](), [nvidia](), [open-source](), [physical-ai](), [physics](), [real-time](), [reinforcement-learning](), [robotics](), [simulation-modeling-design](), [warp](), [world-model]() ### AI overview The article presents NVIDIA's open source, GPU-accelerated Medical Physics Simulation framework for healthcare robotics. It addresses limited medical robotics data, poor generalization, and slow development by enabling anatomical digital twins, device-anatomy and medical imaging simulation, and GPU-scale reinforcement learning within Isaac for Healthcare, Isaac Sim, and Isaac Lab. ### Source excerpt Unlike autonomous driving or industrial robotics, healthcare robotics can't rely on internet-scale data collection or unlimited real-world experimentation.... ## Gemini Robotics 2 brings whole body intelligence to robots DevFeed: [Gemini Robotics 2 brings whole body intelligence to robots]() Original publisher: [Read original article]() Author: Carolina Parada Published: 2026-07-28T13:21:37Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Robotics](), [AI Models](), [Artificial Intelligence](), [vlm](), [multimodal]() Tags: [agent](), [ai](), [ai-models](), [collaboration](), [gemini](), [models](), [multimodal](), [on-device](), [robotics](), [robots](), [teamwork](), [vision]() ### AI overview Gemini Robotics 2 is presented as an intelligence layer for adaptable robots, enabling whole-body control, dexterous manipulation, multi-robot teamwork, and adaptation to new robotic bodies. The article describes three models: a vision-language-action model for motor control, an embodied reasoning vision-language model for communication and multi-step planning, and an on-device model optimized for local operation. ### Source excerpt From feet to fingertips -- we are teaching robots intelligent whole-body control, fine dexterity, and teamwork to complete a broad range of complex tasks. ## NVIDIA Cosmos-H-Dreams: Bringing Real-Time Generative Simulation to Surgical Robotics DevFeed: [NVIDIA Cosmos-H-Dreams: Bringing Real-Time Generative Simulation to Surgical Robotics]() Original publisher: [Read original article]() Author: Lukas Zbinden; Javier Gamazo; Mostafa Toloui; Sean Huver Published: 2026-07-27T09:32:20Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Cosmos](), [Robotics](), [foundation-models](), [real-time](), [Nvidia](), [Synthetic Data Generation](), [synthetic-data](), [data](), [datasets](), [GPU](), [Streaming](), [Inference]() Tags: [cosmos](), [data](), [foundation-models](), [generation](), [generative](), [gpu](), [inference](), [nvidia](), [real-time](), [robotics](), [streaming](), [synthetic-data](), [synthetic-data-generation](), [training]() ### AI overview NVIDIA introduces Cosmos-H-Dreams, a real-time, action-conditioned generative simulator for surgical robotics. The model generates future surgical video from an initial RGB frame and live robot kinematics, enabling interactive closed-loop control, offline policy evaluation, and synthetic data generation. ### Source excerpt World foundation models offer a different path. Instead of manually authoring every object and physical interaction, they learn visual dynamics directly from synchronized video and robot kinematics. NVIDIA's Cosmos-H-Surgical-Simulator demonstrated this approach by generating future surgical video from an initial scene and a sequence of robot actions. It enabled faster-than-physical evaluation and synthetic data generation across the Open-H-Embodiment ecosystem. ## RAISE Summit 2026: What I Learned About AI, Robotics, Agents, and Infrastructure DevFeed: [RAISE Summit 2026: What I Learned About AI, Robotics, Agents, and Infrastructure]() Original publisher: [Read original article]() Author: Alex Razvant Published: 2026-07-25T07:00:53Z Content type: opinion Language: en Sources: [Neural Bits]() Topics: [Artificial Intelligence](), [Physical AI](), [Robotics](), [World models](), [Computer vision]() Tags: [ai](), [conferences](), [models](), [physical-ai](), [robotics](), [vision]() ### AI overview A personal account of RAISE and MACHINA Summit 2026 in Paris, covering conference themes and observations about AI, robotics, embodied AI, world models, perception, and the differences between language-oriented models and models used for robotic perception and action. ### Source excerpt Key takeaways from talks, demos, and conversations at RAISE and MACHINA conferences in Paris this year. ## Grabette: an open system to record robot-manipulation data DevFeed: [Grabette: an open system to record robot-manipulation data]() Original publisher: [Read original article]() Author: Steve Nguyen; Claire Houziel; Gaelle Lannuzel; Simon Le Goff; Jeremy Laville; Étienne Published: 2026-07-21T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Robotics](), [datasets](), [lerobot](), [hugging face](), [Open Source]() Tags: [ai](), [community](), [data](), [datasets](), [devices](), [hugging-face](), [lerobot](), [open](), [open-source](), [robot-manipulation](), [robotics](), [video]() ### AI overview Grabette is an open, low-cost handheld system for recording robot-manipulation demonstrations without requiring a robot, laboratory, or teleoperation rig. It uses a human-operated gripper and cameras to capture demonstrations and produce robot-ready datasets, with browser-based processing and integration with LeRobot and the Hugging Face Hub. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## From Campus to Community Part Two: The Researcher Exodus DevFeed: [From Campus to Community Part Two: The Researcher Exodus]() Original publisher: [Read original article]() Author: Nithya Ruff Published: 2026-07-13T14:07:27Z Content type: opinion Language: en Sources: [Linux Foundation - Blog]() Topics: [Artificial Intelligence](), [linux foundation](), [Open Source](), [Deep learning](), [Computer science](), [Hardware](), [Robotics]() Tags: [ai](), [computer-science](), [deep-learning](), [hardware](), [linux-foundation](), [open-source](), [robotics]() ### AI overview The second part of a Linux Foundation series argues that AI researchers leaving universities for industry jobs, combined with limited academic access to computing resources, is weakening open-source development and academic research. It cites faculty departure data and examples from Carnegie Mellon and other research communities. ### Source excerpt This is a series from Linux Foundation Board Chair, Nithya Ruff. Part One can be found here. ## How to Evaluate General-Purpose Robot Policies for Real-World Deployment DevFeed: [How to Evaluate General-Purpose Robot Policies for Real-World Deployment]() Original publisher: [Read original article]() Author: Brad Nemire Published: 2026-07-12T01:08:17Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Robotics](), [Benchmark](), [foundation-models](), [Simulation and Design](), [Deployment]() Tags: [benchmark](), [benchmarks](), [deployment](), [evaluation](), [featured](), [foundation-models](), [nvidia-research](), [physics](), [robotics](), [simulation-modeling-design](), [testing]() ### AI overview This developer article examines the challenge of rigorously evaluating general-purpose robot policies for real-world deployment. It discusses simulation as a scalable proxy for expensive real-world testing and identifies limitations in current benchmarks, including shared visual sources between training and evaluation, costly Real2sim reconstruction, static task sets, performance saturation, limited failure diagnostics, and uncertainty in success-rate estimates. ### Source excerpt Robotics foundation models have made remarkable progress. Today's best systems can follow natural language instructions to pick, place, sort, and manipulate a... ## Tiny robot boats build floating structures DevFeed: [Tiny robot boats build floating structures]() Original publisher: [Read original article]() Author: Rachel Gordon | MIT CSAIL Published: 2026-07-09T15:50:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Robotics](), [Computer Science and Artificial Intelligence Laboratory (CSAIL)](), [Computer science]() Tags: [alejandro-gonzalez-garcia](), [aquatic-robots](), [architecture](), [artificial-intelligence](), [autonomous-vehicles](), [bioinspiration](), [cities](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [daniela-rus](), [electrical-engineering-and-computer-science-eecs](), [fire-ants](), [floatform](), [floating-infrastructure](), [hybrid-coordination](), [infrastructure](), [machine-learning](), [mit-csail](), [mit-eecs](), [mit-schwarzman-college-of-computing](), [mit-sea-grant](), [mit-sea-grant-program](), [mit-senseable-city-lab](), [modular-robotic-boats](), [modular-self-reconfigurable-robots](), [niklas-hagemann](), [nonlinear-hydrodynamics](), [raft](), [research](), [robot-boats](), [robot-self-assembly](), [robotics](), [robots](), [school-of-architecture-and-planning](), [school-of-engineering](), [science](), [self-reconfiguration](), [senseable-city-lab](), [snap](), [swarm](), [swarm-robots](), [tiny](), [transportation](), [ultrasonic-beacon-system](), [urban-studies-and-planning](), [water](), [wei-wang]() ### AI overview MIT researchers developed FloatForm, a swarm of small robotic boats that can assemble into reconfigurable structures on the water and later break apart and reassemble into new configurations with minimal human direction. ### Source excerpt MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water. ## Introducing Robostral Navigate DevFeed: [Introducing Robostral Navigate]() Original publisher: [Read original article]() Published: 2026-07-08T12:00:59Z Content type: news Language: en Sources: [Mistral AI Blog]() Topics: [Robotics](), [Artificial Intelligence](), [Benchmark](), [Reinforcement learning](), [Simulation and Design]() Tags: [ai](), [benchmark](), [benchmarks](), [model](), [models](), [performance](), [reinforcement-learning](), [robotics](), [robots](), [technology](), [training](), [validation]() ### AI overview Robostral Navigate is an 8B embodied-navigation model that guides robots through complex environments from a single RGB camera and plain-language instructions. It achieves 76.6% success on unseen R2R-CE validation, outperforming systems using depth or multiple cameras, and runs across wheeled, legged, and flying robots. ### Source excerpt Introducing Robostral Navigate: 8B model achieving 76.6% on R2R-CE with just a single RGB camera. No depth sensors, LiDAR, or multiple cameras needed. ## Develop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T DevFeed: [Develop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-07-07T17:05:42Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Robotics](), [Model Development](), [Open Source](), [Training AI Models](), [datasets](), [multimodal](), [Deployment](), [Simulation and Design](), [Tooling]() Tags: [ai-foundation-models](), [apache](), [building](), [data](), [deployment](), [developers](), [development](), [evaluation](), [featured](), [humanoid-robots](), [images](), [integrations](), [isaac](), [isaac-sim](), [manufacturing](), [model](), [multimodal](), [nvidia](), [open-source](), [robotics](), [robotics-simulation](), [robots](), [simulation-modeling-design](), [software](), [tooling](), [training](), [workflows]() ### AI overview NVIDIA Isaac GR00T Development Platform unifies humanoid robot development workflows, combining data collection, simulation-based training, evaluation, and deployment. The article highlights the open Isaac GR00T 1.7 vision-language-action model, which accepts language and images and can be adapted to robots, tasks, and environments through post-training. ### Source excerpt As more teams move from humanoid robot bring-up to task-specific skill development, the need for repeatable development workflows is growing. Building humanoids... [Next page]()