# Robotics Published articles for Robotics. 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... ## CVITEK CV1842H-P-based edge AI camera module offers night vision and AI-ISP support (Crowdfunding) DevFeed: [CVITEK CV1842H-P-based edge AI camera module offers night vision and AI-ISP support (Crowdfunding)]() Original publisher: [Read original article]() Author: Debashis Das Published: 2026-09-16T00:00:55Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Artificial Intelligence](), [Embedded Systems](), [AI Inference](), [V](), [Arm](), [cpu](), [Open Source](), [Ethernet](), [Linux](), [Toit]() Tags: [ai](), [arm](), [artificial-intelligence-ai](), [camera](), [computer-vision](), [cpu](), [debug](), [edge-ai](), [embedded](), [ethernet](), [hardware](), [inference](), [kickstarter](), [linux](), [module](), [open-source](), [real-time](), [risc-v](), [robotics](), [rt-thread](), [soc](), [sophgo](), [tinyml](), [usb](), [video](), [vision]() ### AI overview The AIMORELOGY Ovis is an open-source modular AI vision camera built around the CVITEK CV1842H-P SoC. It provides full-color 1080p night vision, 1.5 TOPS edge AI inference, USB and Ethernet connectivity, and a dual-OS environment using Linux and RT-Thread. ### Source excerpt The AIMORELOGY Ovis is an open-source AI vision camera module built around the CVITEK CV1842H-P SoC, with full-color 1080p night vision and 1.5 TOPS edge AI inference in a compact modular design. It is designed for drones, robotics, security systems, smart cameras, and custom embedded vision products. The camera features a compact stacked design, with a 20 x 20 mm Core board that includes the CVITEK CV1842H-P SoC, 2 Gbit NAND flash, USB, and UART debug pads. A Sensor board with the SC235HAI image sensor connects on top and also adds Ethernet and UART interfaces. An optional CVBS board goes between the Sensor board and the Ovis Core board. AIMORELOGY Ovis specifications: Ovis Core Board SoC - CVITEK CV1842H-P CPU - 1x Arm Cortex-A53 core @ 1.1 GHz, 1x RISC-V C906 core @ 800 MHz NPU - 1.5 TOPS @ INT8 with BF16 support ISP - AI-ISP with real-time 1080p [...] The post CVITEK CV1842H-P-based edge AI camera module offers night vision and AI-ISP support (Crowdfunding) appeared first on CNX Software - Embedded Systems News. ## 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. ## Children's Hospital of Philadelphia Uses Open Source AI and MONAI to Model Pediatric Hearts DevFeed: [Children's Hospital of Philadelphia Uses Open Source AI and MONAI to Model Pediatric Hearts]() Original publisher: [Read original article]() Author: Isha Salian Published: 2026-09-15T09:00:42Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [MONAI](), [Medical imaging](), [Artificial Intelligence](), [Open Source](), [Machine learning]() Tags: [ai](), [ai-for-good](), [healthcare-and-life-sciences](), [machine-learning](), [medical-imaging](), [monai](), [open-source](), [openusd](), [robotics](), [simulation](), [software]() ### AI overview Children's Hospital of Philadelphia uses open source AI tools built on MONAI to generate anatomically precise pediatric heart models from medical images in seconds. Its teams are applying machine learning to support care for children with congenital heart disease. ### Source excerpt Children's Hospital of Philadelphia is using open source AI tools to model children's hearts in seconds -- with the goal of enabling safer, more precise care for kids with congenital heart disease. ## 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 ## MIT researchers develop a generative AI method for enforcing hard constraints in safety-critical applications DevFeed: [MIT researchers develop a generative AI method for enforcing hard constraints in safety-critical applications]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-09-14T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Generative AI](), [AI Models](), [Algorithm](), [Requirements](), [Computer vision](), [Robotics]() Tags: [ai](), [ai-models](), [algorithm](), [algorithms](), [artificial-intelligence](), [computer-science-and-technology](), [computer-vision](), [diffusion-models](), [electrical-engineering-and-computer-science-eecs](), [flow-matching](), [generative-ai](), [hard-constrained-sampling](), [hardflow](), [idss](), [kaveh-alim](), [laboratory-for-information-and-decision-systems-lids](), [machine-learning](), [mechanical-engineering](), [mit-schwarzman-college-of-computing](), [navid-azizan](), [optimal-control](), [paper](), [requirements](), [research](), [robotics](), [safe-ai](), [school-of-engineering](), [trajectory-optimization](), [zeyang-li]() ### AI overview MIT researchers developed a deployment-time technique that lets pretrained generative AI models explore solutions while enforcing hard constraints on final outputs. Experiments in robotics, physical-process control, and computer vision found that the method satisfied required constraints and identified better solutions than existing techniques. ### Source excerpt The "HardFlow" algorithm could help generative AI models produce high-quality outputs that obey strict requirements when "pretty close" doesn't cut it. ## MIT spinout turns plastic waste into resilient building materials DevFeed: [MIT spinout turns plastic waste into resilient building materials]() Original publisher: [Read original article]() Author: Zach Winn | MIT News Published: 2026-09-14T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [systems]() Tags: [3-d-printing](), [ai](), [aj-perez](), [alumni-ae](), [artificial-intelligence](), [atlas-composites](), [cleaner-industry](), [engineering](), [homes](), [housing](), [manufacturing](), [materials-science-and-engineering](), [matt-pouliot](), [mechanical-engineering](), [platform](), [pollution](), [production](), [recycled-plastic-building-materials](), [robotics](), [school-of-engineering](), [startups](), [sustainability](), [u-s-army](), [water]() ### AI overview MIT spinout Atlas Building Composites is commercializing an AI-powered robotic manufacturing platform that recycles single-use and low-grade plastic into durable building components. Its waterless process has been used for structures including a bridge supplied to the U.S. Army Corps of Engineers. ### Source excerpt Atlas Building Composites is commercializing MIT research to turn plastic waste into parts for buildings and other infrastructure. ## Mastering Edge AI on Raspberry Pi with LiteRT and Gemma DevFeed: [Mastering Edge AI on Raspberry Pi with LiteRT and Gemma]() Original publisher: [Read original article]() Author: Lu Wang; Terry Heo; Naushir Patuck; José María Casanova Published: 2026-09-12T11:04:33.891311Z Content type: tutorial Language: en Sources: [Google Developers Blog]() Topics: [LiteRT](), [On-device AI](), [Local AI](), [AI, ML & Data Engineering](), [Google AI](), [cpu](), [Security, Privacy and Abuse Prevention]() Tags: [cli](), [cpu](), [edge](), [gemma](), [gpu](), [inference](), [litert](), [offline](), [on-device](), [real-time](), [robotics]() ### AI overview The article explains how to deploy Gemma models with LiteRT on a Raspberry Pi for local, real-time edge AI applications such as robotics. It highlights LiteRT-LM, CPU and GPU optimization, and reported performance figures for Gemma 4 E2B on Raspberry Pi 5. ### Source excerpt Deploying secure, real-time Edge AI on Raspberry Pi is now simplified using LiteRT and lightweight Gemma open models. LiteRT optimizes CPU and GPU performance, delivering fast token speeds for models like Gemma4, enabling real-time local reasoning for robotics. Developers can quickly convert, quantize, and run these models using the lightweight LiteRT CLI tool. Support for Hailo AI accelerators is also coming very soon. ## Building smarter AMRs with the Arduino® VENTUNO™ Q board DevFeed: [Building smarter AMRs with the Arduino® VENTUNO™ Q board]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-11T11:10:16Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [Arduino](), [Physical AI](), [Microcontroller](), [Linux](), [Computer vision](), [real-time](), [systems]() Tags: [amr](), [arduino](), [autonomous-mobile-robots](), [computer-vision](), [featured](), [linux](), [mcu](), [physical-ai](), [real-time](), [robotics](), [robots](), [ros](), [sensor](), [sensors](), [ventuno-q]() ### AI overview The article explains how Arduino's VENTUNO Q board could support autonomous mobile robots by combining a Linux-capable MPU with a real-time MCU. The MPU can run Linux, ROS 2, navigation, computer vision, and AI workloads, while the MCU handles motor control, encoder feedback, inertial measurements, local sensing, and motor-driver communication. ### Source excerpt Physical AI is based on the idea that intelligence shouldn't stop at perception: instead, it should bring to life systems able to sense their environment, reason about it, and act on it - all in one continuous loop. It's what makes the difference between a device that observes and one that acts. Autonomous mobile robots [...] The post Building smarter AMRs with the Arduino® VENTUNO™ Q board appeared first on Arduino Blog. ## Redesigning a popular robotic arm DevFeed: [Redesigning a popular robotic arm]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-10T17:48:41Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [ESP32](), [3D](), [Code]() Tags: [3d](), [3d-printer](), [arduino](), [components](), [design](), [nano-esp32](), [robot-arm](), [robotic-arm](), [robotics](), [robots]() ### AI overview Arduino Blog describes Kelton Serra's redesigned robotic arm, which uses puppet-style control through potentiometers, an Arduino Nano ESP32, servo motors, and a servo driver board. The redesign aims to make the arm more affordable, easier to build, and better performing, with 3D-printable parts and upgraded wrist and gripper mechanics. ### Source excerpt Robotic arms are extremely versatile, which is the entire point. But that versatility comes at the cost of complexity when it comes to programming and control. A few years ago, Kelton Serra from the Build Some Stuff YouTube channel simplified the situation by giving his custom robotic arm a puppet-style controller. Now he's back with [...] The post Redesigning a popular robotic arm appeared first on Arduino Blog. ## Skild AI Taps NVIDIA Physical AI to Teach Robots New Tasks From a Single Video DevFeed: [Skild AI Taps NVIDIA Physical AI to Teach Robots New Tasks From a Single Video]() Original publisher: [Read original article]() Author: Sasa Docca Published: 2026-09-10T16:30:35Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [foundation-models](), [Cosmos](), [Simulation and Design](), [synthetic-data]() Tags: [ai](), [artificial-intelligence](), [cosmos](), [customer-stories](), [industrial-and-manufacturing](), [isaac](), [model](), [nvidia](), [nvidia-blackwell](), [omniverse](), [physical-ai](), [robotics](), [robots](), [simulation-and-design](), [synthetic-data-generation](), [tensorrt](), [video]() ### AI overview Skild AI's S1 robot foundation model learns new long-horizon physical tasks from a single video demonstration through in-context learning, without task-specific retraining. The article describes its development on NVIDIA AI infrastructure and use of NVIDIA Isaac Lab and Cosmos technologies. ### Source excerpt Manufacturing floors, warehouses and production lines rarely stay fixed -- tasks change, layouts shift and new products arrive, and most robots can't keep up without significant reprogramming. Skild AI's new S1 robot foundation model helps address this, designed to learn previously unseen, long-horizon tasks from a single video demonstration. The model, launched last week, uses [...] ## 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. ## Strengthening Camera Support in Zephyr for Advanced Vision Applications DevFeed: [Strengthening Camera Support in Zephyr for Advanced Vision Applications]() Original publisher: [Read original article]() Author: Zephyr Project Published: 2026-09-04T21:12:17Z Content type: article Language: en Sources: [Zephyr Project]() Topics: [Embedded Systems](), [Embedded Software Dev](), [Open Source](), [Framework](), [Artificial Intelligence](), [object-detection](), [real-time](), [Streaming](), [Robotics]() Tags: [ai](), [blog](), [cameras](), [development](), [embedded](), [embedded-systems](), [events](), [india](), [industry-conference](), [object-detection](), [open-source](), [open-source-summit](), [real-time](), [robotics](), [streaming](), [vision](), [zephyr](), [zero-copy]() ### AI overview This event recap examines proposed changes to Zephyr's camera and driver architecture for AI-driven vision workloads. The proposals include attaching metadata and inference results to individual video buffers and adding per-buffer callbacks to improve buffer ownership, reduce CPU wakeups, and support more manageable camera pipelines. The changes remain under exploration through prototypes and community discussions. ### Source excerpt The Zephyr community came together at Open Source Summit India 2026 in Mumbai to share knowledge and explore developments, tooling, and real-world applications across embedded systems. In this second post event blog, we recap two lightning talks from the Zephyr track focused on camera support. ## An RTOS for Ages Two and Up -- Zephyr Podcast #049 DevFeed: [An RTOS for Ages Two and Up -- Zephyr Podcast #049]() Original publisher: [Read original article]() Author: Benjamin Cabé Published: 2026-09-04T20:01:01Z Content type: article Language: en Sources: [Zephyr Project]() Topics: [Embedded Software Dev](), [Testing](), [Arduino](), [Hardware](), [Maintainers](), [GitHub](), [Robotics](), [Wi-Fi]() Tags: [arduino](), [blog](), [engineering](), [firmware](), [github](), [halow](), [hardware](), [harness](), [maintainers](), [open](), [podcast](), [robotics](), [test](), [zephyr]() ### AI overview Zephyr Podcast episode 049 covers open-firmware hardware that does not yet run Zephyr, hardware-in-the-loop testing with Twister's pytest harness, project growth and contributors, Arduino Core for Zephyr 1.0, maintainer news, new drivers and subsystems, Wi-Fi HaLow support, and Zephyr's robotics community. ### Source excerpt The Dato DUO and the Teenage Engineering catalogue: lovely open-firmware noise machines that do not run Zephyr ...yet! Using the pytest harness in Twister to coordinate a device under test... ## 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. ## Why Output Metrics Can Miss Problems in Complex Production Systems DevFeed: [Why Output Metrics Can Miss Problems in Complex Production Systems]() Original publisher: [Read original article]() Author: Remy Porter Published: 2026-09-02T06:30:00Z Content type: opinion Language: en Sources: [The Daily WTF]() Topics: [Monitoring](), [dashboards](), [robot sense of touch](), [Embedded Software Dev](), [Databases](), [Computer vision]() Tags: [algorithm](), [computer-vision](), [databases](), [embedded](), [feature-articles](), [manufacturing](), [metrics](), [monitoring](), [robotics](), [widget]() ### AI overview This commentary examines a metrics-driven manufacturing team whose automated production line combines robotics, embedded firmware, web-based monitoring tools, and PLC code. It argues that tracking output and limited performance metrics does not adequately explain how such a complex system behaves or why bottlenecks occur. ### Source excerpt Rachel joined a new team which was proudly "metrics driven". When she first met with her boss, Zane, he explained his thinking. "We need to be data-driven to make good decisions, right? We're a manufacturing company. We make widgets. At the end of the day, we need to make the most widgets for the lowest cost of goods sold. So we track that, and that feeds into every decision." The team oversaw an automated production line, which meant the software was a mix of robotics, embedded firmware, high-level web based monitoring tools, and thickets of dreaded PLC code. And because you can't build an entire factory for test purposes, they only way they could test real-world scales with real-world data was to roll changes out to production. They could simulate, they could run tests on subsets of the system, but a change in the production line software couldn't truly be validated until it rolled out into the real world. Rachel's first task on the new team involved making some changes to their metrics dashboard. It was viewed as a good way to get her feet wet with the new team. As it turned out, the metrics dashboard was a Google Sheet, with a complex series of formulas that involved multi-level INDEX functions- essentially querying the spreadsheets like they were a database. Why not use an actual database? Oh, they did -- six actually -- but the company obeyed Remy's Law of Requirements Gathering: "no matter what the requirements the users ask for, what they really wanted was Excel". The database data was pulled into the spreadsheet for reporting. Now, a complicated sheet pulling in data from not one, but six different databases, they must have a pretty complex model to explain how changes to their software would impact productivity. And since they needed to model the software to make predictions about how it'd behave in production, that model must be extremely useful. Of course it wasn't. The only metrics they tracked were output metrics, variations on "widgets produced per unit ## From voice command to robotic arm: how agentic AI on the edge is changing the factory floor DevFeed: [From voice command to robotic arm: how agentic AI on the edge is changing the factory floor]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-01T12:20:24Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [Artificial Intelligence](), [foundation-models](), [Automation](), [Arduino](), [UNO Q](), [AI Agent](), [Physical AI](), [multimodal]() Tags: [agentic-ai](), [ai](), [arduino](), [automation](), [featured](), [foundation-models](), [industrial](), [inference](), [latency](), [manufacturing](), [multimodal](), [robotic-arm](), [robotics](), [smart-factory](), [uno-q](), [usb](), [voice-commands](), [voice-control]() ### AI overview The article describes a demonstration in which Forgis uses a foundation model running on an Arduino UNO Q board to convert voice commands into robotic-arm actions. The system processes multimodal factory data and performs inference locally, enabling real-time control without a cloud round trip. ### Source excerpt For years, bringing real intelligence to industrial automation meant expensive infrastructure, proprietary systems, and steep learning curves. That's changing - fast. Foundation models powerful enough to run at the edge are turning natural language into machine control, and the factory floor is starting to look a lot more like a conversation. AI as the new [...] The post From voice command to robotic arm: how agentic AI on the edge is changing the factory floor appeared first on Arduino Blog. ## Scale AV Perception Across Vehicle Platforms with NVIDIA Omniverse NuRec DevFeed: [Scale AV Perception Across Vehicle Platforms with NVIDIA Omniverse NuRec]() Original publisher: [Read original article]() Author: Michelle Horton Published: 2026-08-31T16:00:00Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Nvidia](), [synthetic-data](), [Simulation and Design](), [data](), [configuration]() Tags: [3d](), [autonomous](), [autonomous-vehicles](), [data](), [developer-tools-techniques](), [developers](), [development](), [model](), [models](), [nvidia](), [omniverse](), [performance](), [physical-ai](), [post](), [robotics](), [scale](), [simulation-modeling-design](), [synthetic-data](), [training](), [tutorial]() ### AI overview This tutorial explains how to adapt an autonomous-vehicle perception stack across carline and sensor-rig variants using existing real-world drives. It presents a four-step workflow with NVIDIA Omniverse NuRec: pair a reconstructed drive with a target rig, render target camera views, refine the frames with NVIDIA Harmonizer, and train a perception model on the output. ### Source excerpt A perception stack is shaped by the vehicle that carries it. Move the same software to a new carline--for example, from an SUV to a sedan or another vehicle... ## ARK Just A Pi - A tiny NDAA-compliant Raspberry Pi CM5 carrier board for drones and robots DevFeed: [ARK Just A Pi - A tiny NDAA-compliant Raspberry Pi CM5 carrier board for drones and robots]() Original publisher: [Read original article]() Author: Jean-Luc Aufranc (CNXSoft) Published: 2026-08-31T10:49:27Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Raspberry Pi](), [Embedded Systems](), [Hardware](), [Ethernet]() Tags: [broadcom-bcmxxxx](), [camera](), [cm5](), [debian](), [drone](), [embedded](), [ethernet](), [hardware](), [hdmi](), [jetson-orin](), [linux](), [raspberry-pi](), [robotics](), [robots](), [sensors](), [som](), [usb]() ### AI overview The article reports on ARK Electronics' Just A Pi, a small NDAA-compliant carrier board for the Raspberry Pi Compute Module 5. It describes its connectors, interfaces, dimensions, weight, supported modules, installation requirements, and pricing. ### Source excerpt ARK Just A Pi is a tiny NDAA-compliant carrier board for the Raspberry Pi CM5 designed for drones, robots, or other space-constrained embedded applications that's about the size of the Compute Module itself. This follows ARK Electronics' NDAA-compliant ARK Jetson Orin NX/Nano bundles introduced in 2024. The new "Just A Pi" is much smaller and lighter, features a built-in 100 Mbps Ethernet switch with two JST-GH Ethernet ports, a micro HDMI port, two MIPI CSI camera connectors, a microSD card slot, a PCIe FFC connector, a USB 3.0 Type-C dual role connector, and a range of small connectors for UART, SPI, PWM, GPIO, and fan. It also features a power connector for the company's PAB power modules. ARK Just A Pi specifications: Supported SoM Raspberry Pi Compute Module 5 - Full support Raspberry Pi Compute Module 4 - The following interfaces are not supported: CSI1/CAM1, UART2, USB-C, PCIe, and fan [...] The post ARK Just A Pi - A tiny NDAA-compliant Raspberry Pi CM5 carrier board for drones and robots appeared first on CNX Software - Embedded Systems News. ## 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. ## How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents DevFeed: [How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-08-26T20:05:06Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Artificial Intelligence](), [Reinforcement learning](), [codex](), [coding](), [Simulation and Design](), [CUDA]() Tags: [agent](), [agentic-ai-generative-ai](), [ai](), [ai-agent](), [ai-agents](), [architecture](), [codex](), [coding](), [cuda](), [development](), [evaluation](), [framework](), [nvidia](), [omniverse](), [physical-ai](), [reinforcement-learning](), [robotics](), [simulation-modeling-design](), [skills](), [testing](), [training](), [tutorial](), [workflow]() ### AI overview This tutorial presents an agent-driven COMPASS workflow for training and evaluating cross-embodiment robot navigation policies. It covers asset preparation, smoke testing, residual reinforcement learning, checkpoint evaluation, runtime integration, and optional reconstructed environments using NVIDIA Omniverse NuRec. ### Source excerpt Navigation enables a robot to turn perception and motion into purposeful autonomy. Unlike locomotion, which produces stable movement, navigation must be used to... ## 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. [Next page]()