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Open-sourcing three repos from our CoRL paper LocoTouch ( 1. Perceptive Learning in IsaacLab ( 2. Policy Deployment (MoCap or onboard sensors) ( 3. Mac Mini for Onboard Robotics ( Yuxiang Yang and I have used the compact Mac Mini and stable deployment pipeline across several legged robot projects (

Changyi Lin

1,010 subscribers

20,087 views • 1 year ago •via X (Twitter)

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2 Comments

Xiatao Sun1 year ago

Amazing work and thank you for open-sourcing everything! The Mac Mini deployment pipeline looks incredibly practical for on-board inference, especially given that we can leverage the unified memory for loading large policies.

Madison Vuong1 year ago

Great contribution to open source, and as a layman it's really exciting to see how tactile sensing can improve robotics.

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After mapping locations using phones (1-3 hours for convenience stores, 1-2 days for larger supermarkets), you can bring robot deployment time from 4-6 weeks down to under a minute. That's why the real world web will onboard the next 100 billion robots and AI.

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Auki

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We're asking for your help to spread the joy. ✨ The proceeds from the gifts will be used to support help alliance projects across several countries. Where: Munich Airport Christmas and Winter Market, MAC between Terminal 1 and Terminal 2 When: December 2nd – January 7th 2024

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Lufthansa

16,912 views • 2 years ago

A 23-year-old runs 3 businesses from a $550 Mac mini and his phone: no team, no office, no employees. He used to pay $15,000/month for a dev team of 5 people. What's running on that mac mini: > 38 specialized agents doing what 5 juniors used to do > 156 skills that fire automatically > One security scanner watching everything 24/7 > A system that learns his coding style over time Claude now writes in his voice automatically and formats outputs his way. The mac mini runs overnight, he checks the results on his phone in the morning. Three businesses, one machine, $20/month, not $15k.

A 23-year-old runs 3 businesses from a $550 Mac mini and his phone: no team, no office, no employees. He used to pay $15,000/month for a dev team of 5 people. What's running on that mac mini: > 38 specialized agents doing what 5 juniors used to do > 156 skills that fire automatically > One security scanner watching everything 24/7 > A system that learns his coding style over time Claude now writes in his voice automatically and formats outputs his way. The mac mini runs overnight, he checks the results on his phone in the morning. Three businesses, one machine, $20/month, not $15k.

Defileo🔮

87,090 views • 5 months ago

Acasis 8-in-1 40Gbps dock turns a Mac Mini into a 2,765 MB/s workstation with one 2TB SSD slot. Hands open the silver case. A Samsung 990 Pro 2TB drops into the single M.2 bay. Lid screws down. The Mac Mini slides in from the side. Two USB4 ports. Three 10Gbps USB-A. HDMI. DisplayPort. SD 4.0. TF 4.0. Power Delivery. Blackmagic Disk Speed Test hits 2,765 MB/s write and 2,812 MB/s read. Every ProRes and H.265 checkbox turns green. Card slots appear as separate drives. 2.45 GB copies in about 4 seconds. Infrared thermometer reads 27.3°C under load. The dock sits on the desk with three monitors running and the original Mac Mini case still closed.

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HodlReaper

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₿RT 𐤊 🐈📈

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Acasis 8-in-1 40Gbps dock turns a Mac Mini into a 2,910 MB/s workstation with one 4TB SSD slot. Hands open the silver case. A Samsung 990 Pro 4TB drops into the single M.2 bay. Lid screws down. The Mac Mini slides in from the side. Two USB4 ports. Three 10Gbps USB-A. HDMI. DisplayPort. SD 4.0. TF 4.0. Power Delivery. Blackmagic Disk Speed Test hits 2,910 MB/s write and 2,945 MB/s read. Every ProRes and H.265 checkbox turns green. Card slots appear as separate drives. 3.82 GB copies in about 5 seconds. Infrared thermometer reads 25.8°C under load. The dock sits on the desk with three monitors running and the original Mac Mini case still closed.

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HodlReaper

16,198 views • 1 month ago

HAO WANG BUILT AN AI SERVER FARM OUT OF 100 MAC MINIS. ONE $599 BOX KILLS A $200/MONTH CLAUDE CODE BILL FOR $3 IN ELECTRICITY a developer posted his $170 claude code bill from 10 days on reddit. someone replied "i bought a mac mini m4. haven't paid anthropic since" the m4 chip has 120 gb/s memory bandwidth and unified memory. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu ollama now supports the anthropic messages api. claude code connects to your local mac mini with one environment variable. zero api costs, same interface a heavy developer pays $459 a month across claude code, chatgpt pro, gemini, cursor and copilot. the mac mini pays off in 3 months and runs on $3 after that uber rolled out claude code to 5,000 engineers and burned $3.4 billion in 4 months. the people who own the hardware in 2026 will look very far ahead in 2028 bookmark this and read the article below

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starmex

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Excited to introduce COLA: Learning Human–Humanoid Coordination for Collaborative Object Carrying 🤝🤖 COLA makes humanoids truly helpful in human collaboration — capable of carrying objects, pushing carts, or responding to human push commands. It provides a proprioception-only policy for compliant human–humanoid coordination across diverse movement patterns. The core idea is simple yet effective: 👉 Fine-tune a collaborative policy from a locomotion policy using a residual teacher. 👉 Train in simulation and distill to a real-world student policy for deployment. Paper: Project:

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X Square Robot

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Igor Kulakov (MicroFactory)

11,428 views • 1 month ago

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Flexion

72,673 views • 1 month ago

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Gipp 🦅

73,740 views • 2 months ago

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Andi Marafioti

56,158 views • 4 months ago

This is what open robotics actually looks like! 🔓 I was in Bordeaux, sitting inside Pollen Robotics, and had a chance to play around with their humanoid robot Reachy 2. It’s expressive, modular, and can even bring you coffee, and of course runs Python or Rust. I was talking with Reachy in 3 different languages, tele-operating it and manipulating kitchen stuff, and make it even mimic my gestures. The best part is that there are no locked APIs, or hidden stuff, just an open platform that you can build upon. The connection with Hugging Face makes it super easy to start, as the open source approach allows everyone to contribute, experiment and add their own things. I already ordered his little brother Reachy Mini, let's see what a robotics rookie can do with that robot! 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

This is what open robotics actually looks like! 🔓 I was in Bordeaux, sitting inside Pollen Robotics, and had a chance to play around with their humanoid robot Reachy 2. It’s expressive, modular, and can even bring you coffee, and of course runs Python or Rust. I was talking with Reachy in 3 different languages, tele-operating it and manipulating kitchen stuff, and make it even mimic my gestures. The best part is that there are no locked APIs, or hidden stuff, just an open platform that you can build upon. The connection with Hugging Face makes it super easy to start, as the open source approach allows everyone to contribute, experiment and add their own things. I already ordered his little brother Reachy Mini, let's see what a robotics rookie can do with that robot! 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

19,433 views • 8 months ago

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Daddy D.O🇳🇬

25,631 views • 1 month ago

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𝗪𝗵𝗮𝘁 𝗶𝗳 𝘆𝗼𝘂 𝗰𝗼𝘂𝗹𝗱 𝗴𝗼 𝗳𝗿𝗼𝗺 𝘁𝗲𝗹𝗲𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗮 𝗿𝗼𝗯𝗼𝘁 𝘁𝗼 𝗱𝗲𝗽𝗹𝗼𝘆𝗶𝗻𝗴 𝗮 𝘁𝗿𝗮𝗶𝗻𝗲𝗱 𝗔𝗜 𝗽𝗼𝗹𝗶𝗰𝘆 𝗶𝗻 𝗹𝗲𝘀𝘀 𝘁𝗶𝗺𝗲 𝘁𝗵𝗮𝗻 𝗶𝘁 𝘁𝗮𝗸𝗲𝘀 𝘁𝗼 𝘄𝗮𝘁𝗰𝗵 𝗮 𝗺𝗼𝘃𝗶𝗲? Today, we're excited to open source our complete example showing exactly that: using Neuracore with the Piper robot from AgileX Robotics. What’s included: • 𝗠𝗲𝘁𝗮 𝗤𝘂𝗲𝘀𝘁 𝘁𝗲𝗹𝗲𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻 – Control your robot with VR • 𝗘𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 – Demo collection to model training to policy deployment • 𝗥𝗢𝗦 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗲𝗿 – See your headset data with a single command • 𝗢𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 𝗠𝗲𝘁𝗮 𝗤𝘂𝗲𝘀𝘁 𝘁𝗲𝗹𝗲𝗼𝗽 𝗽𝗮𝗰𝗸𝗮𝗴𝗲 – Works with any ROS-enabled robot If you have a Piper robot, grab the example, sign up for Neuracore, and show us what you build. Repo: Learn more: Open Robotics Meta Quest

Neuracore

21,894 views • 7 months ago

🔥 JUST IN: Open-source robotics dataset from 100% real-world scenarios! 🤯 Chinese robotics company AGIBOT just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions. Built entirely from real-world environments: commercial spaces, and homes. Collected using AGIBOT G2 robots in free-form collection mode, providing structured, accurately annotated, high-quality data. Digital twin technology creates 1:1 scale replicas in simulation matching the real environments. Both real-world and simulation data are open-sourced. The AGIBOT G2 platform collects multiple data types simultaneously: RGB(D) cameras, tactile sensors, force sensors, LiDAR, IMU, and full-body joint states. Whole-body control coordinates arms, waist, and hands for complex tasks. First-person teleoperation lets operators control the robot from its perspective. The tasks covered are fine-grained manipulation, ultra-long-horizon tasks, spatial navigation, dual-arm coordination, and multi-agent/human-robot collaboration. The dataset includes error-recovery trajectories with annotations. Most datasets only show successful demonstrations. AGIBOT includes failures and how the robot recovers, teaching models how to handle mistakes. After collection, data is tested through policy training and real-robot deployment to ensure quality. Then processed through industrial quality control with multiple screening and cleaning rounds. Making it open-source accelerates embodied AI research by giving researchers access to high-quality real-world robot data at scale. 🇨🇳 Learn more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

🔥 JUST IN: Open-source robotics dataset from 100% real-world scenarios! 🤯 Chinese robotics company AGIBOT just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions. Built entirely from real-world environments: commercial spaces, and homes. Collected using AGIBOT G2 robots in free-form collection mode, providing structured, accurately annotated, high-quality data. Digital twin technology creates 1:1 scale replicas in simulation matching the real environments. Both real-world and simulation data are open-sourced. The AGIBOT G2 platform collects multiple data types simultaneously: RGB(D) cameras, tactile sensors, force sensors, LiDAR, IMU, and full-body joint states. Whole-body control coordinates arms, waist, and hands for complex tasks. First-person teleoperation lets operators control the robot from its perspective. The tasks covered are fine-grained manipulation, ultra-long-horizon tasks, spatial navigation, dual-arm coordination, and multi-agent/human-robot collaboration. The dataset includes error-recovery trajectories with annotations. Most datasets only show successful demonstrations. AGIBOT includes failures and how the robot recovers, teaching models how to handle mistakes. After collection, data is tested through policy training and real-robot deployment to ensure quality. Then processed through industrial quality control with multiple screening and cleaning rounds. Making it open-source accelerates embodied AI research by giving researchers access to high-quality real-world robot data at scale. 🇨🇳 Learn more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

40,583 views • 5 months ago

The first open-source unified world model for scalable robot manipulation: 5B-parameter open-source unified video-action world model that combines policy and world modeling to generate robot actions, predict future visuals, and evaluate task progress from observations, language, and state. The model is trained on 27.3K hours of heterogeneous data (17.8K real-robot teleop, 6.5K UMI demos, 3K egocentric human videos), enabling it to perform complex manipulation tasks like faucet connecting, bag packing, and toolbox storing as shown in demo videos. The approach supports test-time action refinement and points toward deployment-driven continuous improvement via fleet data. Thanks for sharing, Jianlan Luo (Jianlan Luo)! 📌 Resource links for τ0-WM: • Project page: • GitHub (code): • Hugging Face (model weights): • Paper (PDF): ——- Weekly robotics and AI insights. Subscribe free:

The first open-source unified world model for scalable robot manipulation: 5B-parameter open-source unified video-action world model that combines policy and world modeling to generate robot actions, predict future visuals, and evaluate task progress from observations, language, and state. The model is trained on 27.3K hours of heterogeneous data (17.8K real-robot teleop, 6.5K UMI demos, 3K egocentric human videos), enabling it to perform complex manipulation tasks like faucet connecting, bag packing, and toolbox storing as shown in demo videos. The approach supports test-time action refinement and points toward deployment-driven continuous improvement via fleet data. Thanks for sharing, Jianlan Luo (Jianlan Luo)! 📌 Resource links for τ0-WM: • Project page: • GitHub (code): • Hugging Face (model weights): • Paper (PDF): ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

28,276 views • 3 months ago

THIS GUY POWERED A $599 MAC MINI WITH A LAWN MOWER BATTERY AND TURNED HIS TESLA MODEL Y INTO A MOBILE AI OFFICE 00:44 he plugs the mac mini into a green EGO battery through a portable inverter, giving the entire setup its own power source instead of pulling everything from the car. the weird battery is the smartest part. it is normally used for lawn mowers and workshop tools, but here it runs the computer, cables and portable display while the tesla handles the internet connection and cabin. open obsidian, claude code and 4 small agents, and the car becomes a private work pod that can sort 140 links, summarize a 55 minute call and prepare project notes before the next charging stop. the extra setup costs roughly $250 to $350 depending on the battery size. add the inverter, tray, display and cables, and the complete mobile desk lands near $950 before counting the tesla. a larger 56v battery could keep the mac mini running for around 3 to 5 hours during research and writing, or closer to 2 hours with transcription, local models and multiple agents working together. bookmark this before lawn mower batteries start powering better offices than coworking spaces.

THIS GUY POWERED A $599 MAC MINI WITH A LAWN MOWER BATTERY AND TURNED HIS TESLA MODEL Y INTO A MOBILE AI OFFICE 00:44 he plugs the mac mini into a green EGO battery through a portable inverter, giving the entire setup its own power source instead of pulling everything from the car. the weird battery is the smartest part. it is normally used for lawn mowers and workshop tools, but here it runs the computer, cables and portable display while the tesla handles the internet connection and cabin. open obsidian, claude code and 4 small agents, and the car becomes a private work pod that can sort 140 links, summarize a 55 minute call and prepare project notes before the next charging stop. the extra setup costs roughly $250 to $350 depending on the battery size. add the inverter, tray, display and cables, and the complete mobile desk lands near $950 before counting the tesla. a larger 56v battery could keep the mac mini running for around 3 to 5 hours during research and writing, or closer to 2 hours with transcription, local models and multiple agents working together. bookmark this before lawn mower batteries start powering better offices than coworking spaces.

Gipp 🦅

51,881 views • 2 months ago