Your weekly selection of awesome robot videos 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. Summer School on Multi-Robot Systems: 29 July–4 August 2026, PRAGUE Actuate 2026: 18–19 August 2026, SAN FRANCISCO IROS 2026: 27 September–1 October 2026, PITTSBURGH Humanoids Summit Seoul: 22–23 September 2026, SEOUL Enjoy today’s videos! In just six months, our team turned GENE.01 into a fully functional humanoid platform that can walk, sense and interact. Its full-body multimodal skin perceives touch, proximity, force and temperature, bringing Physical AI closer to safe and natural collaboration with people. Not a render. Not a concept. This is GENE.01. The future of Physical AI is taking its first steps. [ Generative Bionics ] Why create robot intelligence for just one hand, when we could have it learn from many? GEN-1, our latest embodied foundation model, now supports a broad range of end effectors from 5-finger hands, to specialized tools, and everything in between. Each hand is a different sensorimotor interface by which GEN-1 experiences the physical world. Scaling pretraining across thousands of these interfaces teaches GEN-1 a universal physical commonsense that transfers to new hands and new ways to grasp, push, pull, twist, and more. And to illustrate this concept, a surprise spatula. [ Generalist ] This paper presents the design, fabrication, and flight validation of a flat-packable flying wing built primarily from corrugated cardboard. The aircraft is manufactured from three laser-cut sheets and assembled through a fold-and lock architecture that forms load-bearing wing structures with minimal tooling and no permanent fasteners. The full airframe can be assembled in under 15 minutes, demonstrating strong potential for rapid deployment, low-cost logistics, and scalable field use. [ AIR Lab ] A $14k open-source data-collection system that includes beat-down capability. [ MEVION ] Thanks, Kento! Together with Niantic Spatial and NVIDIA, [we] can now scan a real deployment site with off-the-shelf hardware, reconstruct it into a photorealistic Gaussian splat, and run massively parallel RL [reinforcement learning] training. The policies trained in our Gym environment then transfer zero-shot to the real robot and environments they were trained for. This enables faster deployment of more capable and robust policies for the end user. [ Flexion ] I don’t know why, but the version of TRON 2 with the stubby little legs is just adorable. [ LimX Dynamics ] Uh, get a real job already...? [ PNDbotics ] Well I guess we can all stop asking what humanoid robots are good for. [ EngineAI ] I think the right thing to do here is only post the disclaimer included with this video: “This film is a conceptual creative production, and certain scenes are presented for demonstration purposes only and do not represent the actual in-store operating process. The final store environment, robot appearance, and functionality are subject to the actual deployment. During actual operations, the robot will autonomously perform only designated preparation steps for specified ice cream products, and its hands will be fitted with protective gloves that comply with applicable food safety requirements.” [ Sharpa ] Drone delivery is now an essential part of the South West London Pathology (SWLP) modernization agenda. Since February 2026, our highly automated aircraft have been delivering urgent NHS samples across south west London, with service up to 85% faster than ground transport. We are thrilled to be part of this initiative, supporting clinicians in providing timely, effective care for patients and contributing to a greener, more resilient NHS. [ Wing ] Take a closer look at what’s next for the Aurora Driver. Designed to move freight farther, faster, and more efficiently, this next generation of the Aurora Driver delivers greater performance, built to last one million miles, and cuts hardware cost in half. [ Aurora ] How does a robot learn to recognize an object it’s never encountered? In this case, a demo can be worth a thousand words. Short human demonstrations can be used to create fully automated training datasets, sidestepping the prompting limitations that hold back vision-language models. Rather than describing objects with language, the system tracks what a person touches and manipulates during a demo, follows those objects through time, and clusters detections to handle objects merging or splitting apart in the scene. This bypasses a core weakness of VLMs, which struggle to reliably detect unusual or novel objects even with repeated, carefully engineered prompts. [ Robotics and AI Institute ]
Unitree's AS2-W wheel-legged robot scales cliffs on reinforcement learning and undercuts Spot by a mile