The Humanoid Hub
@TheHumanoidHub • 115,707 subscribers
Humanoid Robots: Tech, Business, and Social Dynamics. Click the “𝕊𝕦𝕓𝕤𝕔𝕣𝕚𝕓𝕖” button on the profile to support. Run by @dev_and_
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Home robots are coming. The first ones in will be the small ones that are safe around kids and pets. Hugging Face's Pollen Robotics just opened pre-orders for Microduck, a $399 biped. 25cm, under 800g, 15 motors, a camera, a small LiDAR, two IMUs, and an articulated beak that picks things up. Ships with 7 pre-trained behaviors including walking, kicking, and roller skating. Open on GitHub under Apache-2.0: the SDK, the simulator, and the RL training pipeline. So you can teach it new tricks.
The Humanoid Hub768,425 görüntüleme • 6 gün önce
Look at this thing go! 100-meter obstacle course final at the 2026 World Humanoid Robot Games
The Humanoid Hub771,028 görüntüleme • 9 gün önce
A stunning piece of engineering!! 1X unveils the new humanoid hand for NEO - 25 degrees of freedom: 22 fully actuated in the fingers and palm, plus 3 at the wrist. - The DoF are distributed anatomically rather than evenly, deliberately biased toward a thumb that genuinely opposes the fingers. - In-house tendon-driven, quasi-direct-drive running low gear ratios of ~5:1 to 15:1 vs the typical 100:1–200:1. - Motors live in the forearm and pull tendons through the wrist. This keeps the hand light and its inertia low while producing high forces. Sensing - All 25 DoF are natively force-controlled and fully backdrivable. Every joint doubles as a force sensor. - Very important, closed-loop proprioception: it always knows its own pose and effort without looking. - Tactile skin across the fingertips and surfaces measuring contact and shear. This helps with adaptive gripping in real time. Safety and durability - IP68 waterproof and food-safe, so it can wash its own hands. - Compliant by construction: the low gear ratios, tendon drive, and low distal inertia let external impacts safely backdrive the fingers. It yields when hit by a hammer or caught in a drawer. - Full finger assemblies validated to millions of cycles. Manufacturing - Deep vertical integration: in-house motors, custom electronics, and tendon systems. - Hundreds built already, with capacity to produce 10,000 hands this year. "An API to the Physical World"
The Humanoid Hub1,274,584 görüntüleme • 1 ay önce
Never leaving this app, because I know “I’ll be back”
The Humanoid Hub213,357 görüntüleme • 14 gün önce
Sam Altman on the Sources Podcast: OpenAI 'will definitely do humanoids.' It lines up with OpenAI's actual moves: • It's been building an in-house robotics team, with 33 roles currently open in SF, spanning actuator design, data-acquisition ops and embodied AI. • OpenAI shut its original robotics team around 2021, citing a lack of real-world data to train useful systems. Now they're going all in. • Sam Altman has repeatedly signaled his leaning toward the humanoid form in past interviews. OpenAI raised $122B in its latest round, so it has the deepest pockets in the field and pays top dollar for engineers. It's the least talked-about humanoid player, largely due to its secrecy, but likely to be a major force once it fully emerges.
The Humanoid Hub11,639 görüntüleme • 14 saat önce
A battalion of Booster T2s is getting ready for the World Humanoid Robot Games opening ceremony. Now in its 2nd year, the Games run Aug 22-26 in Beijing at the "Ice Ribbon" Olympic oval. It's the biggest yet: ~2,056 robots from 660+ teams across 16 countries, competing in 51 events. Beyond track-and-field style sprints and jumps, this year adds scenario events like robot tug-of-war, weightlifting and pitch-pot. Part sporting event, part real-world capability benchmark for humanoids.
The Humanoid Hub170,302 görüntüleme • 15 gün önce
Humanoid robots can now play tennis in the style of Nadal, Federer, and Djokovic, learned from broadcast footage. AdaPT (Noitom Robotics, Shanghai AI Lab, Dobot, SJTU) extracts professional player motions from TV broadcasts, retargets them to a humanoid, and learns both rallying and serving while preserving each player's distinctive style. The core problem: decoupled planning-and-tracking works in sim but degrades badly on real hardware. Their fix is speed adaptation, training the tracker on randomized execution speeds while the planner learns to adjust motion speed to the incoming ball. Deployed on Unitree G1 and the full-size Dobot Atom. Worth noting on the sensing: the robot has no onboard vision. Ball and robot position both come from external infrastructure, a 35-camera motion-capture arena in the lab. Paper:
The Humanoid Hub85,709 görüntüleme • 13 gün önce
XPENG's next-gen IRON robot effectively crossed the uncanny valley, leading many to believe it was a human in a suit. In a follow-up event to prove it was a robot, He Xiaopeng had its leg skin cut open in front of a live audience. The robot then walked off the stage.
The Humanoid Hub2,146,393 görüntüleme • 10 ay önce
Lots of robot demos at WRC this year. This one stands out for what it's attempting. A Symbiosis Robotics humanoid autonomously drives a go-kart. One take, no stitched clips. The hard part isn't the driving. It's climbing into a confined cockpit, sitting, then coordinating vision, both hands, both feet, and balance through a continuous multi-contact task. They moved from a hierarchical brain-plus-cerebellum architecture to end-to-end control, feeding perception straight into a single model that outputs motion. Fewer cascading errors between layers.
The Humanoid Hub64,177 görüntüleme • 11 gün önce
Dynamic control trained at SUSTech’s ACT Lab in Shenzhen.
The Humanoid Hub1,577,528 görüntüleme • 11 ay önce
Ashok Elluswamy, Tesla's AI lead, during a GTC discussion, highlighting the fundamental similarity in AI approaches for self-driving cars and humanoid robots: - Hierarchical decision making is useful, but it has to be done as part of the same decision-making process as lower-level controls. - We haven't seen the long tail of humanoid robotics, but Tesla has seen the long tail of self-driving, where high and low-level decisions have to be jointly made at a pretty high framerate. - Optimus's architecture is designed in a similar way, where there's a hierarchy but it's all running as part of the same model and the latencies involved in decision making are well modeled. - This architecture will scale quite well with humanoid robots. - The distinction of the decision-making levels is only in the developer's mind. For the model, it's a continuous space of decision making, where there are dials available to make them more fine or coarse. - Humanoids have more sensor modalities and higher degrees of freedom compared to self-driving, but the fundamental constraints remain the same: you need to make real-time decisions. There's obviously a hierarchy to these control signal outputs, but the lowest frequency cannot be too low, because the safety of the robot cannot depend upon things running at very low frequencies.
The Humanoid Hub669,921 görüntüleme • 5 ay önce
Google DeepMind just introduced Gemini Robotics 2. It's a single VLA that unlocks physical dexterity across different end effectors, hands or grippers, from one model checkpoint. Apptronik's Apollo 2 humanoid, with the 22-DoF SharpaWave hand, ties knots and seals a ziplock bag
The Humanoid Hub133,051 görüntüleme • 1 ay önce