{"id":80352,"date":"2026-06-20T15:25:10","date_gmt":"2026-06-20T15:25:10","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/80352\/"},"modified":"2026-06-20T15:25:10","modified_gmt":"2026-06-20T15:25:10","slug":"robot-videos-agentic-ai-robots-quadrupeds-and-more","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/80352\/","title":{"rendered":"Robot Videos: Agentic AI Robots, Quadrupeds, and More"},"content":{"rendered":"

Video Friday<\/a> is your weekly selection of awesome robotics<\/a> 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<\/a> for inclusion.<\/p>\n

RSS 2026<\/a>: 13\u201317 July 2026, SYDNEYSummer School on Multi-Robot Systems<\/a>: 29 July\u20134 August 2026, PRAGUEActuate 2026<\/a>: 18\u201319 August 2026, SAN FRANCISCOIROS 2026<\/a>: 27 September\u20131 October 2026, PITTSBURGH<\/p>\n

Enjoy today\u2019s videos!<\/p>\n

Eno is our first agentic robot: an AI agent and a general-purpose robot working as one system. It reasons, plans, and acts in the real world. Human in capability, not in form. Every detail with a purpose, reduced to what matters. Designed not to resemble us, but to extend us. Eno is built end to end at Genesis.<\/p>\n

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[ Genesis<\/a> ]<\/p>\n

Engineers from NASA\u2019s Jet Propulsion Laboratory are field-testing advanced capabilities for potential future Moon<\/a> and Mars rovers<\/a>. In the Colorado Desert near Plaster City, California, teams used a prototype rover called ERNEST (Exploration Rover for Navigating Extreme Sloped Terrain) to test software for a potential future long-range lunar mission<\/a>. The software enables the rover, developed at JPL<\/a>, to operate autonomously and travel extreme distances with minimal intervention from human operators. <\/p>\n

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ERNEST is a lot more capable than it may look; here\u2019s some recent research showing the kinds of terrain it can handle:<\/p>\n

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[ NASA’s Jet Propulsion Lab<\/a> ]<\/p>\n

Table tennis can produce moments that are difficult even for experienced players to anticipate\u2026like when the ball clips the net and suddenly changes direction. For the Ace research project at Sony AI, these events were a key test of the system\u2019s ability to operate reliably in unpredictable real-world conditions. Ace addresses this uncertainty by simulating counterfactual ball trajectories in real time. In the video, the green overlays show these alternative paths the system considers while planning its response.<\/p>\n

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And check out some of these rallies that the robot has with Miyuu Khiara.<\/p>\n

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[ Sony AI<\/a> ]<\/p>\n

This video of an ANYmal<\/a> deployment in a concrete plant is worth watching because it makes explicit how quadrupeds make money in inspection contexts<\/a>: Among other things, \u201ca cracked crusher foundation [was] caught before a week-long shutdown, avoiding roughly $630,000 in lost production.\u201d That pays for a lot of robots.<\/p>\n

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[ ANYbotics<\/a> ]<\/p>\n

A lot of interesting footage here from GITAI\u2019s prep for a robotic satellite servicing demo mission. The thruster test-firing isn\u2019t a robot, exactly, but it may be the coolest part.<\/p>\n

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[ GITAI<\/a> ]<\/p>\n

Anyone who\u2019s tried to take a half decent photo underwater knows that it\u2019s basically impossible, so let\u2019s try and teach robots to cope.<\/p>\n

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[ Bi-AQUA<\/a> ]<\/p>\n

Thanks, Masato!<\/p>\n

Handling delicate, irregular or unpredictable objects is one of the hardest problems left in automation, and one of the most important. It\u2019s what\u2019s holding back the next wave of robots from doing more in the real world. That\u2019s why we\u2019re working with PSYONIC on a new approach. Their Ability Hand, worn by hundreds of people every day, captures real-world data on touch, pressure and grip. Our GoFa cobot brings the industrial-grade accuracy and repeatability to turn that human data into reliable robotic performance.<\/p>\n

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[ ABB Robotics<\/a> ]<\/p>\n

Sanctuary AI has achieved world-class performance on a complex wire-plugging production task with a global Tier 1 automotive supplier. In this demonstration, Sanctuary AI\u2019s Physical AI successfully performs a high-speed wire-plug insertion task, achieving a validated task success rate of over 99.5% with a cycle time of just 2.54 seconds, meeting live production benchmarks established by the customer.<\/p>\n

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WHY IS THIS STRESSING ME OUT SO MUCH?<\/p>\n

[ Sanctuary<\/a> ]<\/p>\n

This video is quite obviously fake, but I suppose maybe there\u2019s a market for extra beefy quadrupeds? Maybe?<\/p>\n

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[ Kepler<\/a> ]<\/p>\n

I cannot overstate how much I do not want any robot to look at what I\u2019m wearing and then attempt to sell me things based on what it thinks it can guess about my personality or interests.<\/p>\n

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[ MagicLab<\/a> ]<\/p>\n

I am here for fed-up robots learning how to move boxes by just kicking them.<\/p>\n

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[ ATARI Lab<\/a> ]<\/p>\n

Ah, yes, very useful and very important robots that make me very uncomfortable.<\/p>\n

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[ Paper<\/a> ]<\/p>\n

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The idea here is to build an open course around this project, Brit says, \u201cso everyone can experience physical AI right now in a low-risk way.\u201d<\/p>\n

[ GrowBot<\/a> ]<\/p>\n

Thanks, Brit!<\/p>\n

From Your Site Articles<\/p>\n

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