The latest robotics & AI news, aggregated from top sources every 6 hours.
John Black, chief technology officer at Brian Corp, shares insights on how to build trust for robotics fleets and AI. The post From teach and repeat to SelfPath AI: The next robotics leap appeared first on The Robot Report.
Deere beats Q3 expectations, raises guidance, and partners with Reservoir on a $10 million agtech AI initiative. The post Deere faces headwinds in Q3 update and announces Reservoir R&D partnership appeared first on The Robot Report.
The EXL and iMerit executives explain how their companies' combined expertise and platforms will help developers with reliable physical AI. The post EXL acquires physical AI model developer iMerit appeared first on The Robot Report.
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.Humanoids Summit Seoul: 22–23 September 2026, SEOULIROS 2026: 27 September–1 October 2026, PITTSBURGHCoRL 2026: 9–12 November 2026, AUSTINEnjoy today’s videos! NVIDIA just paid US$12.9 billion dollars for the company that acquired Pollen Robotics, and this must be why.Meet Microduck. 🦆 The 25 cm, 780 g robot that waddles, falls, gets back up, and learns new tricks.Packed inside: 15 degrees of freedom, a front camera, an 8x8 LiDAR, two IMUs, mics, a speaker, NFC, Wi-Fi and Bluetooth.Out of the box, Microduck already walks, sits, crouches, roller skates, picks up objects with its articulated beak, and recovers from falls on its own. Drive it with a game controller, plug in accessories and NFC tagged objects, run autonomous behaviors, or gather several Microducks for races and football. Software fully open source. Ready for whatever you throw at it. On pre-order for an astonishingly low $399, and ships before Christmas.[ Microduck ]Thanks, Matthieu!If you’ve chosen to ignore all of the earlier DARPA Lift Challenge videos that we’ve posted, now you can get all caught up in about five minutes.[ DARPA ]You had me at “54-gram robot that out jumps a kangaroo.”[ IEEE Transactions on Robotics ]Sometimes, you just need a video like this.Most fish-inspired robots are built for one size and one job, so scaling them up or down usually means starting from scratch. A team of engineers says it’s found a way to solve that problem. They’ve unveiled ScaFi, a robot modeled on fish like cod and mackerel.[ New York University ]Thanks, Leah!Martin writes, “We’re a small robotics team in Czechia, Europe building practical hardware around the Unitree G1. Here’s a short demo of our lightweight gripper picking up a strawberry; the gripper weighs under 200 g and is designed for simple, sensitive manipulation without adding a complex multi-finger hand.[ Sentio Robotix ]Thanks, Martin!Hybrid visual markers that are useful for both cameras and lidar is a neat idea.[ Hello Robot ]Thanks, Binit!EmoLo brings emotion-inspired expressive locomotion to Open Duck Mini V2, a low-cost open-source bipedal robot inspired by Disney’s BDX droids. With a single reinforcement learning policy, the robot can generate distinct walking styles associated with different emotional expressions, showing how characterful and expressive whole-body motion can be achieved on an accessible robotic platform.[ EmoLo ]Thanks, Masato!If it’s possible for a robot with a completely immobile face to look frustrated, this robot absolutely does starting at three minutes into this video.[ DLR RM ]Noble Machines deployed its first general-purpose robots to a Fortune Global 500 industrial customer within 18 months of the company’s launch and met its first delivery milestone, made possible by its AI-driven whole-body control and industry-leading end-to-end autonomy.[ Noble Machines ]We’ve reduced the time it takes to go from physical prompt → robot behavior. The faster anyone can teach a robot to do something new, the easier it becomes to scale physical work.[ Generalist ]I know this video is mostly a gimmick, but I would totally rent a moderately heavy lift quadruped for a couple of days to help with a move.[ DEEP Robotics ]Is taking two minutes to excellently fold a shirt too long, or do we even care how long it takes, as long as it’s a robot doing it?[ Tokyo Robotics ]TRON 2 × Wuji Hand 2 handles TCM pharmacy work: picking, weighing, grinding and packaging. The omnidirectional base frees the hands, while precise gripping and dual-arm force control enable mid-air operations.[ LimX Dynamics ]Person who genuinely knows things about robots, Christian Hubicki, explains everything about robots smashing into walls.[ Christian Hubicki ]
Locus Robotics recently acquired Nexera Robotics, which create unique soft picking technology, bolstering its manipulation capabilities. The post How Locus is getting a grasp on one of robotics biggest challenges: manipulation appeared first on The Robot Report.
The group infected more than 1,000 organizations in a relentless supply-chain attack campaign.
Action from the 11 vs 11 humanoid match at RoboCup 2026. Photo credit: RoboCup Federation. RoboCup 2026 saw history made, as two teams of 11 humanoids took to the soccer field, the first time a full complement of robots has competed. The game saw B-Human (Bremen, Germany) take on HTWK Robots (Leipzig, Germany), with both […]
Teradyne Robotics sued cobot maker JAKA over alleged patent infringement, marking its second battle with a Chinese cobot company in 2026. The post Teradyne Robotics ramps up fight against cobot copycats appeared first on The Robot Report.
One of the new NSF funded centers will be the Center for Human and Robot Co-Adaptation, led by The University of Texas at Austin. The post NSF to invest $90M into three new technology centers, including one focused on robotics appeared first on The Robot Report.
Presented by Gravitee Agent complexity is the insidious shadow lurking inside enterprises right now that needs a light shone on it.That’s because enterprises don't deploy a single agent and watch it run, they deploy fleets, each one calling APIs, calling other agents, reaching into applications that were never built with a machine decision-maker in mind. That's the failure mode that should keep you up at night: a windy, complicated system nobody can see clearly enough to govern. But why do things get so opaque so quickly?Add a second agent to a system, and you've added one connection. Add a tenth, and you haven't added ten connections, you've potentially added dozens, because now any agent might call any other, and each of those calls can trigger a call somewhere else. Complexity doesn't creep up with agent headcount. It compounds with the number of paths between agents, and nobody's job is to draw that graph. A support ticket that used to touch one system might now pass through four agents before a human ever lays eyes on it, and every one of those handoffs is a decision point nobody approved.Most enterprise AI programs stall when the humans responsible for their agents lose the thread. Ask a security team a simple question: which agents can reach which systems, and watch the silence. Ask which agent triggered which downstream action three hops ago. More silence.The instinct is to treat this like a checklist. Approve the agent. Log the agent. Move on. I'd argue this is the wrong instinct. A checklist checks a single point in time. Complexity runs across a chain, and you can't govern a chain with a stack of one-time approvals any more than you can call a diet successful because you had a vegetable once.So where does it actually break down?Permissions creep first. Somebody builds an agent to summarize support tickets, grants it broad API access because scoping it properly would've taken another sprint, and forgets about it. Six months later, that same agent has a path into the payments system. Nobody remembers signing off on that. Nobody did.And ownership thins out the further the chain runs. Five agents touch one workflow, something breaks at step four, and now you're asking who's responsible for a link nobody was ever assigned to own, because the org chart stopped at "deploy the agent" and never got to "name the human who answers for it."This is a story about governance infrastructure that hasn't caught up with how agents actually behave: interconnected, cascading, multiplying faster than the processes built to track them.Fixing the cluster starts with identity. Every agent needs to exist as its own entity, not a shadow permission borrowed from whoever deployed it. Its own name in the register. Its own scoped authority. A named human sponsor who answers for what it does. That part is necessary.But it is nowhere near sufficient.The harder piece is the oversight that holds across the entire chain, not just at each individual link in it. You need to see what an agent did, what it set off downstream, and where that trail ends in real time, not in a report someone pulls together once a quarter. Get agent-level identity right and stop there, and you end up with a filing cabinet full of perfectly documented agents operating inside a system nobody can actually explain.And oversight by itself only tells you what already happened. Watching a chain isn't the same as controlling it. Enforcement is the piece most programs skip: the ability to stop an out-of-policy call before it executes, not just log it for someone to find in a review three weeks later. A dashboard that shows you an agent breached its scope five minutes ago is a monitoring tool. A system that stops the breach from happening in the first place is governance. Enterprises serious about agent accountability need both, and most have only built the first.We're all running at blazing speed to ensure we're not the ones left behind in the race we've found ourselves in, and we're all too aware that there's a cost to slowing down. Every enterprise serious about agentic AI hits the complexity wall eventually. The ones that get past it are the ones who built enough visibility and accountability, so their fleet can keep growing without anyone losing the ability to answer one question: what is this system doing right now, and who's responsible for it.But don't miss the point. Complexity isn't a reason to pump the brakes. The enterprises getting this right aren't slowing down. They're building toward Human-Agent Harmony, where scale and accountability grow together instead of trading off against each other.The real risk was never a single agent doing exactly what it was built to do. It's a hundred of them doing exactly that, all at once, interacting in combinations nobody designed for. That kind of multiplication is what keeps enterprise AI stuck running pilots forever instead of running production.Solve for complexity and autonomy stops being the villain. It starts being the whole point.Rory Blundell is CEO at Gravitee. Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.
227 install commands were found in corporate docs pointing at code nobody owns.
Carbon Robotics introduced a plant foundation AI model and tractor kit, enabling farmers to customize laser weeding. The post Carbon Robotics partners with iMerit to power instant in-field AI customization appeared first on The Robot Report.