Video Friday: Digit Learns to Dance—Virtually Overnight
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. ICRA 2026 : 1–5 June 2026, VIENNA RSS 2026 : 13–17 July 2026, SYDNEY Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Enjoy today’s videos! Getting Digit to dance takes more than putting on some fancy shoes–our AI Team can teach Digit new whole-body control capabilities overnight. Using raw motion data from mocap, animation, and teleop methods, Digit gets new skills through sim-to-real reinforcement training. [ Agility ] We’ve created GEN-1, our latest milestone in scaling robot learning. We believe it to be the first general-pur
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
ICRA 2026: 1–5 June 2026, VIENNA
RSS 2026: 13–17 July 2026, SYDNEY
Summer School on Multi-Robot Systems: 29 July–4 August 2026, PRAGUE
Enjoy today’s videos!
Getting Digit to dance takes more than putting on some fancy shoes–our AI Team can teach Digit new whole-body control capabilities overnight. Using raw motion data from mocap, animation, and teleop methods, Digit gets new skills through sim-to-real reinforcement training.
[ Agility ]
We’ve created GEN-1, our latest milestone in scaling robot learning. We believe it to be the first general-purpose AI model that crosses a new performance threshold: mastery of simple physical tasks. It improves average success rates to 99% on tasks where previous models achieve 64%, completes tasks roughly 3x faster than state of the art, and requires only 1 hour of robot data for each of these results. GEN-1 unlocks commercial viability across a broad range of applications—and while it cannot solve all tasks today, it is a significant step towards our mission of creating generalist intelligence for the physical world.
[ Generalist ]
Unitree open-sources UnifoLM-WBT-Dataset—high-quality real-world humanoid robot whole-body teleoperation (WBT) dataset for open environments. Publicly available since March 5, 2026, the dataset will continue to receive high-frequency rolling updates. It aims to establish the most comprehensive real-world humanoid robot dataset in terms of scenario coverage, task complexity, and manipulation diversity.
[ Hugging Face ]
Autonomous mobile robots operating in human-shared indoor environments often require paths that reflect human spatial intentions, such as avoiding interference with pedestrian flow or maintaining comfortable clearance. This paper presents MRReP, a Mixed Reality-based interface that enables users to draw a Hand-drawn Reference Path (HRP) directly on the physical floor using hand gestures.
[ MRReP ]
Thanks, Masato!
Eye contact, even momentarily between strangers, plays a pivotal role in fostering human connection, promoting happiness, and enhancing belonging. Through autonomous navigation and adaptive mirror control, Mirrorbot facilitates serendipitous, non-verbal interactions by dynamically transitioning reflections from self-focused to mutual recognition, sparking eye contact, shared awareness, and playful engagement.
[ ARL ] via [ Cornell University ]
Experience PAL Robotics’ new teleoperation system for TIAGo Pro, the AI-ready mobile manipulator designed for advanced research. This real-time VR teleoperation setup allows precise control of TIAGo Pro’s dual arms in Cartesian space, ideal for remote manipulation, AI data collection, and robot learning.
[ PAL Robotics ]
Utter brilliance from Robust AI. No notes.
[ Robust AI ]
Come along with our Senior Test Engineer, Nick L., as he takes us on a tour of the Home Test Labs inside the iRobot HQ.
[ iRobot ]
By automating the final “magic 5%” of production—the precise trimming of swim goggles’ silicone gaskets based on individual face scans—UR cobots allow THEMAGIC5 to deliver affordable, custom-fit goggles, enabling the company to scale from a Kickstarter sensation to selling over 400,000 goggles worldwide.
[ Universal Robots ]
Sanctuary AI has once again demonstrated its industry-leading approach to training dexterous manipulation policies for its advanced hydraulic hands. In this video, their proprietary hydraulic hand autonomously manipulates a lettered cube, continuously reorienting it to match a specified goal (displayed in the bottom-left corner of the video).
[ Sanctuary AI ]
China’s Yuxing 3-06 commercial experimental satellite, the first of its kind to be equipped with a flexible robotic arm, has recently completed an in-orbit refueling test and verification of key technologies. The test paves the way for Yuxing 3-06, dubbed a “space refueling station,” to refuel other satellites in orbit, manage space debris, and provide other in-orbit services.
[ Sanyuan Aerospace ] via [ Space News ]
This is a demonstration of natural walking, whole-body teleoperation, and motion tracking with our custom-built humanoid robot. The control policies are trained using large-scale parallel reinforcement learning (RL). By deploying robust policies learned in a physics simulator onto the real hardware, we achieve dynamic and stable whole-body motions.
[ Tokyo Robotics ]
Faced with aging railway infrastructure, a shrinking workforce and rising construction costs, Japan Railway West asked construction innovator Serendix to replace an old wooden building at its Hatsushima railway station using its 3D printing technology. An ABB robot enabled the company to assemble the new building in a single night ready for the first train service the next day.
[ ABB ]
Humanoid, SAP, and Martur Fompak team up to test humanoid robots in automotive manufacturing logistics. This joint proof of concept explores how robots can streamline operations, improve efficiency, and shape the future of smart factories.
[ Humanoid ]
This MIT Robotics Seminar is from Dario Floreano at EPFL, on “Avian Inspired Drones.”
[ MIT ]
This MIT Robotics Seminar is from Ken Goldberg at UC Berkeley, on “Good Old-Fashioned Engineering Can Close the 100,000 Year “Data Gap” in Robotics.”
[ MIT ]
Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
modeltrainingavailable![[R], 31 MILLIONS High frequency data, Light GBM worked perfectly](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-neural-network-P6fqXULWLNUwjuxqUZnB3T.webp)
[R], 31 MILLIONS High frequency data, Light GBM worked perfectly
We just published a paper on predicting adverse selection in high-frequency crypto markets using LightGBM , and I wanted to share it here because the findings are directly relevant to anyone dealing high frequency data and machine learning The core problem we solved: Every market maker's nightmare — getting picked off by informed traders right before a big move. We built a model that flags those toxic seconds before they wreck you. The data: - 31,081,463 second-level observations of BTC/USDT perpetual futures on Bybit - February 2025 → February 2026 (381 raw daily files) - Strict walk-forward regime, zero lookahead bias The key results (this is the part that shocked us): Our TailScore metric — which combines predicted toxicity probability with predicted price move severity — flags the top
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Products
![Considering NeurIPS submission [D]](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-robot-hand-JvPW6jsLFTCtkgtb97Kys5.webp)
Considering NeurIPS submission [D]
Wondering if it worth submitting paper I’m working on to NeurIPS. I have formal mathematical proof for convergence of a novel agentic system plus a compelling application to a real world use case. The problem is I just have a couple examples. I’ve tried working with synthetic data and benchmarks but no existing benchmarks captures the complexity of the real world data for any interesting results. Is it worth submitting or should I hold on to it until I can build up more data? submitted by /u/Clean-Baseball3748 [link] [comments]




Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!