Move the target. The robot finds it again. This visual grasping pipeline combines #IntelRealSenseD405 + #reBotArmB601-RS + #ROS2 + #YOLOE: Detection → Depth → Hand-Eye Calibration → Grasp Pose → Pick & Place Move the pen, and the system detects its new position, calculates a new grasp pose, and sends the arm to pick and place it. The Seeed Wiki walks through the full #visualgrasping workflow — from camera & ROS setup to detection, calibration, grasp validation and the final grasp-and-place pipeline. wiki.seeedstudio.com/rebot_a…

Introducing OM-1, our first robot foundation model: zero-shot generalizing across table-top arms, industrial arms, and humanoids. - Learned directly from human manipulation data - No teleop or robot data - Near human-level dexterity and efficiency - Multi-robot collaboration

we are testing out the integration with @LeRobotHF task: place the robstride 00 motor in its packaging learn more: makermods.ai/maker-arm

What's Inside Watti? This Lamp Is Packed With Hardware at $700 Watti's current prototype is basically a small robotics platform disguised as a desk lamp. At the center is a Raspberry Pi 5, connected to 5 RobStride motors for movement and 45 individually addressable WS2812 RGB LEDs for lighting. For vision, it uses an Orbbec Astra Mini S RGB-D camera, capturing RGB + depth at 640×480 @ 30 FPS. The five axes control the base, shoulder, elbow, neck and head, while motor position feedback lets Watti know its current pose. Power comes from an external 24V/10A supply, with a Geekworm X735 V3 handling the conversion to 5V for the Pi.

Anyone using Robstride drivers and wanting a rust or MCU version of them I released a crate for this exact purpose! Check it out: github.com/HIRO-Industries/R… Full no_std so your MCU can use it. I’m using mine with a CAN hat on an RPI

From #Simulation to Reality: Build Your Own Physical AI Pipeline with Seeed #reBot Arm🤖Glad to dive deep and develop this course with @NVIDIARobotics team! Learning now: seeedstudio.com/sim-to-real-… The goal isn’t just to reproduce a single #robot demo. It’s to provide a reusable, open, and reproducible architecture for #PhysicalAI development—one that can be extended to new tasks, environments, datasets, and robot embodiments.

🤖 From natural language to physical action. At #WRC 2026, we’re showcasing #reBot B601-RS × #VLM Skills—an agentic Physical AI system powered by #NVIDIA #Cosmos 3-Edge and 21 native Action Skills. Perceive → Reason → Plan → Act → Observe → Recover Moving beyond scripted #robot toward adaptive, closed-loop #PhysicalAI. 🦾 📍 WRC 2026 · Booth A435 📅 Aug 19–23 · Beijing Read more: seeedstudio.com/blog/2026/08…

#WRC 2026 Day 1 was a blast!🤖 At Booth A435, @seeedstudio × @RobStride_com are showcasing how #reBot B601-RS goes beyond scripted actions with #VLM Skills—turning natural-language goals into closed-loop Perceive → Reason → Plan → Act → Recover workflows, making reBot more agentic! We’re also launching our new Physical AI course, collaborated with the #NVIDIA, taking developers from simulation to real-world #VLA deployment with reBot arm + NVIDIA #saac. Check full course at: seeedstudio.com/sim-to-real-… Huge thanks to the @NVIDIARobotics team for the continued support! 🙌 Come see Agentic #PhysicalAI in action at WRC 2026, Booth A435, Aug 19–23 in Beijing, China!

🤖 Bring your reBot Arm into the simulation world with @nvidia #Isaac Sim 6.0! Before building #PhysicalAI applications, setting up a reliable simulation environment is the first step. This guide walks you through: ✅ Isaac Sim 6.0 installation on Ubuntu ✅ Environment configuration ✅ Launch verification ✅ Preparing your robot simulation workflow Start exploring #robotlearning, #manipulation, and digital twin applications with reBot Arm: seeedstudio.com/reBot-Arm-B6…