During @AutomateShow in Chicago I had a pleasure to speak with @chrismatthieu about their new stuff! @RealSenseai launched Perception Studio alongside the D585 Pro that is an AI studio for developers building perception systems for robots. Three initial features, with more coming. → Visual Inertial Odometry: Legged robots need to understand their own motion without wheel encoders clicking. VIO lets them track position using camera and IMU data. Hard problem. The studio shows developers how to do it. → Close-range vision: The D585 Pro normally sees 6 meters. Now it can also see 12 centimeters. That 6cm-to-6m range is massive. Humanoids can perceive a screw on a table and navigate a room. Same camera. Different capability. → Built-in people detection: Robots need to know when humans are nearby for safety. The studio includes this out of the box. RealSense is releasing tools to developers early, getting feedback before the tech hardens. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Really glad I finally got to visit @XSquareRobot. We got an early look at XRZero-G0, their open-source full-body data collection and training system that works without requiring a physical robot body. At the time it hadn’t been officially released yet, so we couldn’t share anything haha. Now they’ve officially launched the QUANXTA Zero series — a robot-free embodied data production platform. This is not just a hardware setup. It’s a full-stack system that connects data collection, high-fidelity synchronization, automatic cleaning, intelligent annotation, embodied model training, robot inference, and evaluation loops — all in one pipeline. The goal is very clear: close the “last mile” gap between data and models, and build scalable infrastructure for embodied AI. QUANXTA Zero comes in three setups for different capture scenarios: → G1 (UMI-VIO): dual grippers with a head-mounted rig, balancing quality, usability, and endurance → G0 (UMI-VR): full-body mobile data capture → E0 (Ego): lightweight head-mounted setup for first-person data collection In short, it’s building the data foundation for embodied intelligence. Data is what drives intelligence emergence in large models — both scale and quality matter. If the data flywheel is already spinning, real home robots might be closer than we think. @TheHumanoidHub @dolylupec

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