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Announcing the first production robot navigation framework on $500 hardware Explore the world once → your robot agent will relocalize and build a persistant, spatial memory across sessions SLAM, relocalization, loop closure, map i/o, planning, control No ROS. Open source.

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stash

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53,361 просмотров • 3 дней назад •via X (Twitter)

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Your Openclaw / Agent can now control multiple robots in realtime. We’ve abstracted and standardized all hardware and control interfaces so your agent can run our spatial tool calls on ANY robot. Fleet command of humanoid, quadruped, xARM, and Piper arm in unison. Fully open source.
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Your Openclaw / Agent can now control multiple robots in realtime. We’ve abstracted and standardized all hardware and control interfaces so your agent can run our spatial tool calls on ANY robot. Fleet command of humanoid, quadruped, xARM, and Piper arm in unison. Fully open source.

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Booster Robotics has launched Booster Studio, the first IDE built specifically for embodied AI. > Booster Studio features code editing, high-precision simulation, real-robot debugging, and real-world deployment. > It shortens the path from the first idea to the working hardware, with the build, test, and deployment loop living in a single environment rather than scattered across separate tools. Vibe Robotics 👀

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Another win for open-source robotics! 🔥 Hugging Face just released a fully open-source humanoid robot, and you can build one for $2,500. I'm a huge advocate of open-source in robotics space. Why? Robotics is too hard to solve alone. So lowering the entry point is crucial. Also, ROS proved open ecosystems create lasting industry standards. So let's have a look at the new member of humanoids family! LeRobot Humanoid is a 3D-printed, bipedal humanoid platform designed for real robot learning experiments. It's a complete and, buildable robot Anddddd yes, it's a full stack release: → Hardware files, bill of materials and full assembly documentation → Simulation assets and training environments → Runtime tools for calibration and real-world control → Sim-to-real identification pipeline When a part breaks, reprint it. When a design choice doesn't work, modify it and test again. The whole point is fast iteration on real hardware, not treating the robot as a fixed artefact. The timing is not a coincidence. As foundation models for robotics mature, the field desperately needs open physical platforms to train, validate and deploy them on. clem 🤗 LET'S GO!!! Build it here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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New demo of #OpenClaw + #ROS + AgenticROS all running locally on a Radxa X4 Robot Operating System (ROS) robot!
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New demo of #OpenClaw + #ROS + AgenticROS all running locally on a Radxa X4 Robot Operating System (ROS) robot!

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We built a GPT-4o-powered cleaning robot. - $250 for the robot arms - 4 days to build Open source is truly democratizing the field of robotics. Kaspar Janssen

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ROSClaw Integration Update Read the text in the video carefully ⊙ Robot is present both physically can in Nvidia Isaac Sim simulation. ⊙ The agent’s initial goal set to explore any object it finds in its spatial view. ⊙ Think of it as if the physical robot is seeing through the simulation. ⊙ ROSClaw vision uses Gemini Live for spatial narration ⊙ An object (a playground slide) is identified and the ROSClaw (OpenClaw) agent takes over. ⊙ The agent initiates action. Attempts to walk towards object. ⊙ None of it is pre-planned. The agent (robot) is acting on its own
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ROSClaw Integration Update Read the text in the video carefully ⊙ Robot is present both physically can in Nvidia Isaac Sim simulation. ⊙ The agent’s initial goal set to explore any object it finds in its spatial view. ⊙ Think of it as if the physical robot is seeing through the simulation. ⊙ ROSClaw vision uses Gemini Live for spatial narration ⊙ An object (a playground slide) is identified and the ROSClaw (OpenClaw) agent takes over. ⊙ The agent initiates action. Attempts to walk towards object. ⊙ None of it is pre-planned. The agent (robot) is acting on its own

Irvin (in Japan 🇯🇵)

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Qwen-VLA feels like one of the first real robotics foundation models. A single system trained across robot manipulation, navigation, egocentric human video, simulation, and vision-language reasoning instead of isolated robot policies.
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Qwen-VLA feels like one of the first real robotics foundation models. A single system trained across robot manipulation, navigation, egocentric human video, simulation, and vision-language reasoning instead of isolated robot policies.

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