Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
Ammo Changes Everything: The Real Breakthrough Behind Unitrix G1’s Human-Like Intelligence
In just the past few days, the robotics world has exploded with news that sounds completely unreal. Except, it’s all completely real. Unitrix G1 Humanoid just got a major upgrade with a system called Ammo that lets it clean your house, pick up toys, open the fridge, and even load the dishwasher like it’s been living with you for years.
Their B2 robot dog now got redesigned for firefighting, with a water cannon that can blast foam nearly 200 feet. Lenovo stepped into the game with its first humanoid, Legion No. 1, which performed Tai Chi live on stage and answered real-time business questions.
And Beijing just announced it’ll be hosting the World Humanoid Robot Sports Games this August, inside actual Olympic venues, with robots competing in track, gymnastics, and even soccer. So let’s talk about it. Alright, by now pretty much everyone in the robotics space knows the Unitrix G1, but what really flipped the narrative wasn’t the hardware, it was Ammo.
And not just some marketing buzzword, Ammo, or Adaptive Motion Optimization, is probably the most advanced real-time, whole-body control system we’ve seen on a consumer-level humanoid. It’s what turned G1 from an impressive machine into a robot that genuinely understands how to move like a living thing. Most robots struggle with complex motion, because humanoid bodies are hard to control.
You’ve got 29 degrees of freedom, nonlinear physics, contact dynamics, all of that makes it extremely difficult to balance flexibility with stability. Older methods relied on rigid control systems or motion capture data that didn’t really translate well into dynamic environments. They’d train robots to copy how people move, but not how people adjust in real time.
Inside AMO: The Brain Behind G1’s Human-Like Adaptability and Motion Mastery
That’s where Ammo changes everything. AMO is built differently. It combines reinforcement learning and trajectory optimization in a way that lets the robot not only learn how to move, but how to adapt on the fly.
First, the system runs millions of motion tests in simulation using sim-to-real learning, so the robot can fail over and over without breaking anything. It learns how to pick things up off the ground, reach high shelves, twist its torso, crouch low, or even stretch sideways without losing balance. Then, those lessons get translated into real-world behavior that works, not just in theory, but in your kitchen.
So, when you see G1 bend down to pick up a toy, or carefully adjust its balance to slide a bottle onto a high shelf, that’s AMO in action. It’s controlling the robot’s entire body, legs, torso, waist, everything, based on an internal plan, not just isolated joint movements. And it does this in real time, responding to changes in its environment and adapting to unpredictable inputs.
You can even throw it into a teleoperation mode using a VR headset, and it’ll track your movements like a shadow. But what’s crazy is that once you let go, it doesn’t freeze. It keeps going.
It understands the goal and keeps executing, smoothly transitioning from human guidance to autonomous action. Under the hood, AMO uses what’s called a Hybrid Motion Synthesis Pipeline. That means it blends human-like arm movements from motion capture data with sampled torso commands to generate new kinds of whole-body actions that weren’t even in the original data sets.
From Imitation to Intelligence: How AMO Teaches G1 to Move Beyond Its Limits
The robot isn’t just imitating, it’s generalizing. Whether it’s yaw, pitch, roll, or height control, AMO gives the G1 way more flexibility than previous systems. For instance, it doesn’t rely solely on waist motors to tilt the upper body.
Instead, it shifts its legs, bends the knees, and uses full-body posture to reach angles that older robots couldn’t even attempt. There’s also a ton of work behind the scenes to make sure this control works out of distribution, which basically means G1 can handle commands and situations it never saw before. You can tell it to stretch further, crouch lower, or rotate more than it was trained to, and it still finds a way to do it.
One test had it picking up baskets from both sides at floor level, then walking forward and placing them on a shelf at eye level. That kind of full-bodied coordination, from crouching to twisting to reaching to placing, used to be science fiction. AMO makes it routine.
In fact, they ran detailed evaluations comparing AMO to older control strategies. Across the board, yaw, pitch, roll, base height tracking, it outperformed everything else. Even when pushed into untrained territory, AMO showed minimal tracking error.
That means the robot wasn’t just guessing, it was adapting with precision. In trash-throwing tasks, it smoothly twisted its torso 90 degrees and nailed the throw. In another setup, it picked up a paper bag by aligning its torso, maneuvering its hand through the loop, and then lifting and placing it without losing grip or posture.
The whole system worked with both teleoperation and full autonomy, depending on the task. What’s even more impressive is how AMO builds that behavior. During training, they use a two-stage learning framework.
Beyond Humanoids: Unitry’s B2 Firefighting Robot Dog Redefines First Response
A teacher policy gets access to all the ideal data, then a student policy learns from that in a more restricted setup, basically mimicking what the robot would experience in the real world. This approach lets the final system perform reliably without needing perfect conditions. So yeah, this isn’t your average walking bot.
The G1 with AMO isn’t just reacting, it’s planning, adjusting, and executing complex tasks that most robots still fumble. It stretches, crouches, twists, walks, balances all while coordinating 29 joints across its entire body. And with AMO driving it, you don’t get that weird mechanical stiffness you usually see, you get motion that feels smooth, deliberate, and honestly kind of human.
This is where humanoid robotics is heading. Not just mobility, but full-body dexterity with the kind of responsiveness that makes real-world deployment finally possible. But Unitry didn’t stop there.
They’ve now got a four-legged firefighting robot dog, a modified version of their B2 robot, and it’s actually made for emergency scenarios. This firefighting version comes with a water or foam cannon that can shoot up to 60 meters away at 40 liters per second. That’s intense.
Its joints are upgraded by 170% over the regular model, so it can climb obstacles up to 15 inches and handle steep stairs at a 45-degree angle. Perfect for broken buildings and chaotic scenes. And it’s not just muscle.
The B2 firefighting dog is loaded with tech, live video, lidar sensors, and communication gear for sending updates to human teams. It has a built-in cooling sprinkler system to survive the heat, plus swappable batteries that won’t mess with its waterproofing. This thing is meant to go where humans can’t.
Lenovo Enters the Arena: Le Xiong No.1 and the Rise of Humanoid Sports at the Olympics
Collapsed buildings, toxic zones, zero visibility areas. It can map surroundings, locate fires, carry modules, even support rescue operations. Now let’s jump from the real world into the corporate world.
Lenovo just entered the humanoid robot race, and they’re not playing around. At their Techworld 2025 event in Shanghai, they unveiled Le Xi
Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News’
ong No.1, calling it a Silicon Employee. This wasn’t just a press statement.
They put it on stage and had it perform a Tai Chi routine. Yeah, not just walking or standing. Actual, slow, balanced martial arts, live.
During the Q&A, the robot was pulling data from Lenovo’s systems in real time and answering questions like a trained rep. Under the hood, this robot runs on three core intelligent frameworks. It can understand and communicate across devices naturally, access both public and private knowledge across ecosystems, and perform advanced tasks with autonomy.
Everything’s layered over a secure design, and it’s all running on Lenovo’s hybrid architecture, device, edge, cloud, and network. This means data collection, processing, and AI model training all happen seamlessly across platforms. But Lenovo’s not just showing off.
They’re planning real-world use cases. You’ll be seeing this robot in eldercare and healthcare environments soon. And in August, they’re bringing it to compete in the Beijing Humanoid Robot Sports Games, which yes, is an actual thing now.
The event is going down at Beijing’s two biggest Olympic venues, the Bird’s Nest and the Ice Ribbon, from August 15th to 17th. This isn’t a gimmick either. There will be 11 actual human sports recreated by humanoid robots.
From Marathons to Motion Mastery: How Atom and China’s Robot Games Are Shaping the Future of Humanoids
Track and field, football, gymnastics, and more. Robotics experts and sports professionals teamed up to create events that mimic human movement as closely as possible. And the goal is clear.
Refine mechanical structure and push motion algorithms further through real performance under pressure. This is the second major robot sports event in China this year. The first was a humanoid half-marathon in April.
20 robots lined up to run over two hours straight, and one of them, Qiankong Ultra, finished first after nearly two hours and 40 minutes. That wasn’t just about endurance. That was a massive benchmark for stability, safety, and real-world readiness in complex environments.
The whole event became a testing ground for robots from different companies, validating their ability to operate outside the lab. Now while all this is happening in public arenas, let’s zoom back into the research lab. There’s another robot making waves.
This one’s called Atom, developed by a team at P&D Botics in China. What sets Atom apart is the way it walks. It doesn’t just move.
It walks like a human, adapting its stride, balance, and pace on the fly across uneven terrain. This is thanks to its proprietary reinforcement learning system combined with imitation learning. Atom has been in development since mid-2023, and they’ve upgraded nearly every part of it since.
From Labs to Life: Why 2025 Marks the Breakout Year for Real-World Humanoid Robotics
The legs and feet are reinforced for durability, and the actuators are modular so it can handle all sorts of unpredictable environments. It runs on a full-stack system powered by an Intel i7 chip with real-time controls and full-body motion architecture. It’s got 25 force-controlled QDD actuators with legs delivering up to 360 newton-meters of torque.
The arms have 5 degrees of freedom, the waist has 3, and the robot stands 1.6 meters tall, weighing 60 kilograms. What’s really clever is how it learns. It’s been trained with NVIDIA’s Isaac Gym, using deep reinforcement learning at scale.
Then, they used motion capture to feed in extremely precise human movements, adapted the data to Atom’s body, and fine-tuned everything. It doesn’t rely on vision for now, it’s mostly focused on blind locomotion. But even without vision modules, it’s already adapting dynamically to whatever you throw at it.
We’re talking full-on simulation-to-reality transition, something many robots still struggle with. Meanwhile, we’re seeing the broader robotics industry coming together for massive exhibitions. The World Robot Conference is also happening in Beijing this August, just before the Robot Sports Games.
This year’s event will have more than 200 companies participating and around 100 new product launches. It’s going to be co-hosted by major international groups like the World Federation of Engineering Organizations and EU Robotics. And yes, humanoid robots are the main focus this time, not just as novelty, but as scalable solutions for everything from rescue missions to healthcare.
So if you’re looking at all this and wondering where it’s headed, the answer is pretty clear. We’re moving beyond the demo phase. Not just futuristic, not just experimental, useful.
Let me know in the comments if you had a robot like G1 or Atom, what’s the first thing you’d have it do in your house? And yeah, maybe we’ll cover Phantom’s next upgrade once that $100 million lands. Thanks for reading, and I’ll catch you in the next one.
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
- Unitree Just Gave Its ROBOT a BRAIN and It’s Already Acting HUMAN + More AI & Robotics News
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