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This week, Amazon introduced Vulcan! 🌋 Amazon has created a new robot called Vulcan, and it's the first one with a real sense of touch. I visited one of the fulfillment centers of Amazon to shoot their latest picking robot for you! Vulcan doesn’t just “see” like most robots—it... can also feel what it’s touching, like a human hand. 🪬 This helps it do tricky tasks, such as picking items out of crowded bins, without damaging anything nearby. Vulcan is powered by physical AI, which means it uses both sight and touch to understand and move through the world. In Amazon’s warehouses, items are stored tightly in small compartments, which used to be hard for robots to handle. Their new system with Universal Robots arms changes that, it can gently pick up or place items in these tight spaces by knowing how much pressure to apply. The robot uses special tools and sensors to know when it touches something and how hard it’s pressing. 🤏🏼 It helps make the workplace safer by doing tasks that used to require employees to use ladders or reach overhead. Over time, Vulcan will become even smarter by learning from its mistakes and gaining more experience, just like a person does.show more

Lukas Ziegler

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16,413 görüntüleme • 1 yıl önce •via X (Twitter)

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@amazon Congratulations 👏

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Feeling like a sitting duck in today's cyberstorm? ⛈️ "CYBERSECURITY DICTIONARY For Everyone" equips leaders with the knowledge to understand cyber threats & make solid security decisions. Protect your company & build resilience🤝 Available at Amazon: 🛒

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@amazon Very interesting. Slow though?

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Huge congratulations to the team at @amazon on unveiling Vulcan... this is a serious leap forward for robotics and physical AI! This is how we reclaim industrial leadership: by building real capability into machines that work with us, not just around us. Touch, precision, safety, and learning... Vulcan checks every box. It’s not just a fulfillment upgrade. It’s a symbol of what American innovation looks like when we bet big and build bold. Let’s build!

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@amazon Is this sold? Or just for them?

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@amazon How does this compare to a more humanoid form factor? Looks quite rigidly programmed. Maybe the efficiency could be improved with embodied ai solutions

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@amazon Vulcan is a total game changer! Excited to see how this tech evolves.

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The main robotics invention Amazon made to help automate 75% of its fulfilment center is called the Vulcan system. An AI-powered gripper has the “sense of touch”, which can handle 75% of Amazon’s 1 million unique items. The previous picking robots used machine vision and suction cups but couldn’t “feel” the items (they were built to handle packages and covered <60% of warehouse items). Per CNBC, the new Vulcan gripper uses sensors and generative AI to apply different force to different items (eg. soft on bag of candies vs. hard on textbook). It also uses AI for solving stacking puzzles to minimize wasted space in a box (like Tetris).

The main robotics invention Amazon made to help automate 75% of its fulfilment center is called the Vulcan system. An AI-powered gripper has the “sense of touch”, which can handle 75% of Amazon’s 1 million unique items. The previous picking robots used machine vision and suction cups but couldn’t “feel” the items (they were built to handle packages and covered <60% of warehouse items). Per CNBC, the new Vulcan gripper uses sensors and generative AI to apply different force to different items (eg. soft on bag of candies vs. hard on textbook). It also uses AI for solving stacking puzzles to minimize wasted space in a box (like Tetris).

Trung Phan

350,308 görüntüleme • 7 ay önce

Very cool breakthrough by our physical AI and robotics teams-- Vulcan is the first robot that combines sight and touch, and can feel its way through cluttered spaces the way humans do. Vulcan is helping make work safer by handling ergonomically challenging tasks, while creating opportunities for our teammates to grow their skills in robotics maintenance.

Very cool breakthrough by our physical AI and robotics teams-- Vulcan is the first robot that combines sight and touch, and can feel its way through cluttered spaces the way humans do. Vulcan is helping make work safer by handling ergonomically challenging tasks, while creating opportunities for our teammates to grow their skills in robotics maintenance.

Andy Jassy

143,932 görüntüleme • 1 yıl önce

AMAZON’S NEW ROBOT “FEELS” — AND IT’S CHANGING WHAT HUMAN WORK LOOKS LIKE Meet Vulcan, Amazon’s latest warehouse bot that can “feel” what it picks up—grabbing high and low shelves, climbing ladders, and handling the repetitive strain stuff that usually sends people to physical therapy. Amazon says robots now touch 75% of customer orders—and they’re training warehouse staff to become robot techs, floor monitors, and reliability engineers. Not just new roles—new job categories. No, it’s not a 1:1 swap: not everyone wants to be a robot whisperer. But the idea that warehouse jobs are locked into the same routine forever? Also gone. Think of it like the PC revolution: the shift from manual labor to managing machines. Not less work—just different work. This isn’t a Competition between men and machines. It’s about learning to work smarter with them. Source: Amazon / TechCrunch

AMAZON’S NEW ROBOT “FEELS” — AND IT’S CHANGING WHAT HUMAN WORK LOOKS LIKE Meet Vulcan, Amazon’s latest warehouse bot that can “feel” what it picks up—grabbing high and low shelves, climbing ladders, and handling the repetitive strain stuff that usually sends people to physical therapy. Amazon says robots now touch 75% of customer orders—and they’re training warehouse staff to become robot techs, floor monitors, and reliability engineers. Not just new roles—new job categories. No, it’s not a 1:1 swap: not everyone wants to be a robot whisperer. But the idea that warehouse jobs are locked into the same routine forever? Also gone. Think of it like the PC revolution: the shift from manual labor to managing machines. Not less work—just different work. This isn’t a Competition between men and machines. It’s about learning to work smarter with them. Source: Amazon / TechCrunch

Mario Nawfal

372,533 görüntüleme • 1 yıl önce

🚨 Apple joins the robotics race! Researchers from Carnegie Mellon University and Apple have developed a robot collision avoidance system. They called it ARMOR and they implemented it on the Fourier GR-1 robot. What is ARMOR? 👘 ARMOR is a system that helps humanoid robots "see" their surroundings better by using small, smart depth sensors placed on their arms. It solves the problem of blind spots and occlusions in traditional robot perception, making robots much safer and more efficient. It uses Time-of-Flight (ToF) sensors to detect obstacles, providing a near-complete view of the robot’s environment. 🔭 A smart software powered by transformer-based AI learns from human movements to help robots plan their actions dynamically. ARMOR reduces collisions by an impressive 63.7%, making robots significantly better at navigating crowded or complex spaces. The system is fast as well! 💨 ARMOR-Policy cuts computational time by 26× compared to traditional planning methods, ensuring robots can act quickly. P.S. Thoughts on this? The research paper is in the comments! ~~~ ♻️ RT to help 1 robot find a new workplace.

🚨 Apple joins the robotics race! Researchers from Carnegie Mellon University and Apple have developed a robot collision avoidance system. They called it ARMOR and they implemented it on the Fourier GR-1 robot. What is ARMOR? 👘 ARMOR is a system that helps humanoid robots "see" their surroundings better by using small, smart depth sensors placed on their arms. It solves the problem of blind spots and occlusions in traditional robot perception, making robots much safer and more efficient. It uses Time-of-Flight (ToF) sensors to detect obstacles, providing a near-complete view of the robot’s environment. 🔭 A smart software powered by transformer-based AI learns from human movements to help robots plan their actions dynamically. ARMOR reduces collisions by an impressive 63.7%, making robots significantly better at navigating crowded or complex spaces. The system is fast as well! 💨 ARMOR-Policy cuts computational time by 26× compared to traditional planning methods, ensuring robots can act quickly. P.S. Thoughts on this? The research paper is in the comments! ~~~ ♻️ RT to help 1 robot find a new workplace.

Lukas Ziegler

169,366 görüntüleme • 1 yıl önce

🇨🇦 ROBOT HANDS JUST LEVELED UP IN CANADA Sanctuary AI showed off a robotic hand that uses hydraulic power to grip, twist, and move like a real one. The hand can handle delicate objects, like dice, without crushing them, proving robots are getting scary precise. Hydraulic actuation gives the robot smoother, stronger control, making it better for heavy industrial work and tricky small tasks. This could change how robots work in factories, warehouses, or even in jobs too dangerous for humans. The future of robot hands? Less clunky claws, more human-like grip power with machine muscle. Source: Wevolver

🇨🇦 ROBOT HANDS JUST LEVELED UP IN CANADA Sanctuary AI showed off a robotic hand that uses hydraulic power to grip, twist, and move like a real one. The hand can handle delicate objects, like dice, without crushing them, proving robots are getting scary precise. Hydraulic actuation gives the robot smoother, stronger control, making it better for heavy industrial work and tricky small tasks. This could change how robots work in factories, warehouses, or even in jobs too dangerous for humans. The future of robot hands? Less clunky claws, more human-like grip power with machine muscle. Source: Wevolver

Mario Nawfal

50,661 görüntüleme • 9 ay önce

Not all automation needs an arm 🦾I That’s right, AmbiRobotics just released their new product - a palletizing gantry system. It’s called AmbiStack, and at first glance, it looks like a 3D tetris. 🥞 It’s a mechanical system designed to automate the stacking and packing of items in warehouses. The system uses Sim2Real reinforcement learning and advanced AI vision technology to optimize how items are sorted and stacked. Even without prior knowledge of their size, shape, or appearance. 📦 AmbiStack can stack items densely onto pallets or into walled containers, maximizing space and reducing warehouse transportation costs. It is a multipurpose solution that can be used for different applications, such as building pallets for retail distribution or stacking items directly on the floor. The system is highly adaptable, able to handle both single-SKU and mixed-SKU cases, and can stack items in any orientation for maximum flexibility. AmbiStack features multi-pick-and-place capabilities, allowing it to pick and place multiple items at once, significantly improving workflow efficiency. P.S. Yes, I know that gantry is technically a three-axis robot.

Not all automation needs an arm 🦾I That’s right, AmbiRobotics just released their new product - a palletizing gantry system. It’s called AmbiStack, and at first glance, it looks like a 3D tetris. 🥞 It’s a mechanical system designed to automate the stacking and packing of items in warehouses. The system uses Sim2Real reinforcement learning and advanced AI vision technology to optimize how items are sorted and stacked. Even without prior knowledge of their size, shape, or appearance. 📦 AmbiStack can stack items densely onto pallets or into walled containers, maximizing space and reducing warehouse transportation costs. It is a multipurpose solution that can be used for different applications, such as building pallets for retail distribution or stacking items directly on the floor. The system is highly adaptable, able to handle both single-SKU and mixed-SKU cases, and can stack items in any orientation for maximum flexibility. AmbiStack features multi-pick-and-place capabilities, allowing it to pick and place multiple items at once, significantly improving workflow efficiency. P.S. Yes, I know that gantry is technically a three-axis robot.

Lukas Ziegler

24,133 görüntüleme • 1 yıl önce

The robot is learning several novel tasks instantly, after just ONE demonstration each... Instant Policy makes it possible: no extra training, no weight updates, just pure in-context learning. It just got accepted at ICLR 2025, and it’s changing how robots learn. With just a single demo, a robot can pick up a new task and start performing it right away. Why this is a big deal: ✅ Learns tasks instantly with just one or a few demonstrations ✅ Improves over time as more demonstrations are given ✅ Uses simulation-based training with “pseudo-demonstrations” for scalability ✅ Can transfer skills across different robots and even follow language-defined tasks It brings in-context learning to robotics, opening up new possibilities for flexible, real-world automation. You can try it yourself: code and weights are available at • • • • Thank you to Edward Johns, Director of the Robot Learning Lab at Imperial College for sharing their work! 🙏

The robot is learning several novel tasks instantly, after just ONE demonstration each... Instant Policy makes it possible: no extra training, no weight updates, just pure in-context learning. It just got accepted at ICLR 2025, and it’s changing how robots learn. With just a single demo, a robot can pick up a new task and start performing it right away. Why this is a big deal: ✅ Learns tasks instantly with just one or a few demonstrations ✅ Improves over time as more demonstrations are given ✅ Uses simulation-based training with “pseudo-demonstrations” for scalability ✅ Can transfer skills across different robots and even follow language-defined tasks It brings in-context learning to robotics, opening up new possibilities for flexible, real-world automation. You can try it yourself: code and weights are available at • • • • Thank you to Edward Johns, Director of the Robot Learning Lab at Imperial College for sharing their work! 🙏

Ilir Aliu

46,285 görüntüleme • 1 yıl önce

Touch: A Game-Changer in Dexterity for Robots You can’t be responsive to the world if you can’t feel it. That’s true for people—and it's just as true for robots. We’re zeroed in on a practical, yet innovative, approach to creating general purpose robots designed to perform physical work. And that means hands, powered not just by vision, but by touch. Vision alone falls short. There are many instances where our vision is obstructed while performing work tasks–like grabbing items out of a bin–you lose line of sight. You need tactile intelligence—texture, pressure, contact—with real-time feedback to move faster, smarter, and with confidence. Watch a full explainer video on Sanctuary AI’s latest touch sensors on our blog: #Robotics #AI #HumanoidRobots #Dexterity #TactileSensing #SanctuaryAI

Touch: A Game-Changer in Dexterity for Robots You can’t be responsive to the world if you can’t feel it. That’s true for people—and it's just as true for robots. We’re zeroed in on a practical, yet innovative, approach to creating general purpose robots designed to perform physical work. And that means hands, powered not just by vision, but by touch. Vision alone falls short. There are many instances where our vision is obstructed while performing work tasks–like grabbing items out of a bin–you lose line of sight. You need tactile intelligence—texture, pressure, contact—with real-time feedback to move faster, smarter, and with confidence. Watch a full explainer video on Sanctuary AI’s latest touch sensors on our blog: #Robotics #AI #HumanoidRobots #Dexterity #TactileSensing #SanctuaryAI

Sanctuary AI

53,217 görüntüleme • 1 yıl önce

🚨BREAKING: A new humanoid robot straight out of Europe! Kinisi has introduced their humanoid robot called KR1. This robot has a base with wheels instead of legs. This provides much greater stability and safety for human workers. It’s built for warehouse and factory tasks like picking, stacking, and moving goods. It supports payloads up to 15 kg, runs 8 hours per charge with hot-swappable batteries, and docks itself for recharging. The robot can lift heavy boxes from high shelves, handle fragile items without damage, and adapt its arm trajectories on the fly to avoid obstacles. In demos, it moved smoothly between shelves, placed items into totes, and transported them across the warehouse, all autonomously. Great retrofitting potential, because it doesn’t require major infrastructure changes to deploy. It learns from simple demonstrations, operates offline for reliability and privacy, and integrates quickly into existing workflows. Let’s not forget that E-commerce is growing rapidly, with global online sales expected to reach nearly $7 trillion by 2025. As more people shop online, the number of packages being shipped each day is soaring. These robots help us to make sure they will be delivered on time! 📦

🚨BREAKING: A new humanoid robot straight out of Europe! Kinisi has introduced their humanoid robot called KR1. This robot has a base with wheels instead of legs. This provides much greater stability and safety for human workers. It’s built for warehouse and factory tasks like picking, stacking, and moving goods. It supports payloads up to 15 kg, runs 8 hours per charge with hot-swappable batteries, and docks itself for recharging. The robot can lift heavy boxes from high shelves, handle fragile items without damage, and adapt its arm trajectories on the fly to avoid obstacles. In demos, it moved smoothly between shelves, placed items into totes, and transported them across the warehouse, all autonomously. Great retrofitting potential, because it doesn’t require major infrastructure changes to deploy. It learns from simple demonstrations, operates offline for reliability and privacy, and integrates quickly into existing workflows. Let’s not forget that E-commerce is growing rapidly, with global online sales expected to reach nearly $7 trillion by 2025. As more people shop online, the number of packages being shipped each day is soaring. These robots help us to make sure they will be delivered on time! 📦

Lukas Ziegler

23,245 görüntüleme • 8 ay önce

A Switzerland-based startup Flexion has created a robotic brain that helps the Unitree G1 move smoothly and work on its own. It uses reinforcement learning, where the robot trains in simulations to learn walking, balancing, and picking objects. In tests, it cleaned a space by finding and placing items in a basket without human help.

A Switzerland-based startup Flexion has created a robotic brain that helps the Unitree G1 move smoothly and work on its own. It uses reinforcement learning, where the robot trains in simulations to learn walking, balancing, and picking objects. In tests, it cleaned a space by finding and placing items in a basket without human help.

Space and Technology

17,545 görüntüleme • 2 ay önce

One of the why questions we’re always asking is how can we help operations employees access inventory more efficiently? We’re taking a big leap forward by introducing DeepFleet, an exciting new AI model that makes our one million+ robot fleet work smarter. Think of DeepFleet as an intelligent traffic management system for our fulfillment centers. Just like smart traffic systems reduce congestion in cities, DeepFleet coordinates our robots’ movements to find optimal paths and reduce bottlenecks. By leveraging our deep expertise in robotics and combining it with AWS tools like SageMaker, we’ve built an AI model that learns from our extensive data on inventory movement to make real-time decisions that improve robot travel time by 10% (which at our scale is pretty significant). What makes this particularly exciting is how AI and robotics create value across the board. For customers, it means faster delivery times and lower costs. For employees, it opens up new opportunities – our robots handle physically demanding tasks and heavy lifting, making our fulfillment centers safer, while our people take on more technical roles. This combination of robotics and generative AI is just getting started, and am looking forward to what we’ll invent next.

One of the why questions we’re always asking is how can we help operations employees access inventory more efficiently? We’re taking a big leap forward by introducing DeepFleet, an exciting new AI model that makes our one million+ robot fleet work smarter. Think of DeepFleet as an intelligent traffic management system for our fulfillment centers. Just like smart traffic systems reduce congestion in cities, DeepFleet coordinates our robots’ movements to find optimal paths and reduce bottlenecks. By leveraging our deep expertise in robotics and combining it with AWS tools like SageMaker, we’ve built an AI model that learns from our extensive data on inventory movement to make real-time decisions that improve robot travel time by 10% (which at our scale is pretty significant). What makes this particularly exciting is how AI and robotics create value across the board. For customers, it means faster delivery times and lower costs. For employees, it opens up new opportunities – our robots handle physically demanding tasks and heavy lifting, making our fulfillment centers safer, while our people take on more technical roles. This combination of robotics and generative AI is just getting started, and am looking forward to what we’ll invent next.

Andy Jassy

42,327 görüntüleme • 11 ay önce

The $10k robot arms that can learn from a handful of demos: Most robots still lose the cost equation. They’re slow, expensive, and take months to deploy, which means… they only make sense for huge factories. The The Robot Learning Company (YC X25) is building affordable, general-purpose robot arms that can pick up new tasks from just a few human demonstrations. Why it matters: ✅ Under $10k per pair of stationary arms ✅ Adapts to new tasks with imitation + reinforcement learning ✅ Deployable in days, not months From small manufacturers to service providers, this makes robotic labor accessible to companies that could never justify it before. Saying hi to founder Jannik Grothusen 👋 More here:

The $10k robot arms that can learn from a handful of demos: Most robots still lose the cost equation. They’re slow, expensive, and take months to deploy, which means… they only make sense for huge factories. The The Robot Learning Company (YC X25) is building affordable, general-purpose robot arms that can pick up new tasks from just a few human demonstrations. Why it matters: ✅ Under $10k per pair of stationary arms ✅ Adapts to new tasks with imitation + reinforcement learning ✅ Deployable in days, not months From small manufacturers to service providers, this makes robotic labor accessible to companies that could never justify it before. Saying hi to founder Jannik Grothusen 👋 More here:

Ilir Aliu - eu/acc

36,336 görüntüleme • 10 ay önce

This is Delta, a deformable multirotor robot developed by scientists at the University of Tokyo that can both fly and roll using its flexible body design. It uses a thrust control system to move efficiently in the air and on the ground, allowing it to adapt to different environments. This capability makes it useful for tasks like disaster response and long-duration operations, introduced in 2024.

This is Delta, a deformable multirotor robot developed by scientists at the University of Tokyo that can both fly and roll using its flexible body design. It uses a thrust control system to move efficiently in the air and on the ground, allowing it to adapt to different environments. This capability makes it useful for tasks like disaster response and long-duration operations, introduced in 2024.

Space and Technology

26,325 görüntüleme • 2 ay önce

🇨🇭 BADMINTON-BOT TAKES THE COURT IN SWITZERLAND A Swiss team built a four-legged robot that plays badminton against humans and actually returns shots like it means it. Created with ETH Zurich, this bot uses artificial intelligence to teach itself how to move, see, and hit the shuttlecock with freakish precision. It learns through reinforcement learning which is a fancy way of saying it fails over and over until it figures things out. A special vision system helps it track the birdie while running around like a robot goat with a grudge. It even adjusts its movement to avoid messing up its own view. Researcher, Yuntao Ma: "We believe that this project demonstrates the potential of artificial intelligence to advance legged robots in complex tasks, paving the way for advances in autonomous and intelligent systems, including humanoids. The control algorithm generalizes to other robotic platforms such as humanoids, as well as to other tasks such as search and rescue and home services." Source: Telegrafi Media Source: The Independent On Youtube

🇨🇭 BADMINTON-BOT TAKES THE COURT IN SWITZERLAND A Swiss team built a four-legged robot that plays badminton against humans and actually returns shots like it means it. Created with ETH Zurich, this bot uses artificial intelligence to teach itself how to move, see, and hit the shuttlecock with freakish precision. It learns through reinforcement learning which is a fancy way of saying it fails over and over until it figures things out. A special vision system helps it track the birdie while running around like a robot goat with a grudge. It even adjusts its movement to avoid messing up its own view. Researcher, Yuntao Ma: "We believe that this project demonstrates the potential of artificial intelligence to advance legged robots in complex tasks, paving the way for advances in autonomous and intelligent systems, including humanoids. The control algorithm generalizes to other robotic platforms such as humanoids, as well as to other tasks such as search and rescue and home services." Source: Telegrafi Media Source: The Independent On Youtube

Mario Nawfal

76,687 görüntüleme • 1 yıl önce

What if robots could learn real-world tasks from your perspective… without ever touching a robot? This is a system that trains robot policies using nothing but human-first, egocentric video data from smart glasses. No robots, no teleop, no sensors, just humans doing real tasks in the real world. Why it matters ✅ Learns robot policies from 20 minutes of human video; zero robot demos ✅ Generalizes to new objects, views, and even robot morphologies ✅ Uses 3D points for interpretable, spatially grounded learning ✅ Deploys directly to real-world robots with strong zero-shot success Thank you, Vincent Liu, for sharing!!! Learn more here: 🔗 Paper: 🌐 Website: 📍 BOOKMARK FOR LATER

What if robots could learn real-world tasks from your perspective… without ever touching a robot? This is a system that trains robot policies using nothing but human-first, egocentric video data from smart glasses. No robots, no teleop, no sensors, just humans doing real tasks in the real world. Why it matters ✅ Learns robot policies from 20 minutes of human video; zero robot demos ✅ Generalizes to new objects, views, and even robot morphologies ✅ Uses 3D points for interpretable, spatially grounded learning ✅ Deploys directly to real-world robots with strong zero-shot success Thank you, Vincent Liu, for sharing!!! Learn more here: 🔗 Paper: 🌐 Website: 📍 BOOKMARK FOR LATER

Ilir Aliu - eu/acc

10,509 görüntüleme • 1 yıl önce

Hands are as important as the brain. From Shenzhen, Stella Robot has unveiled the PANTHEON HAND 22:a new generation of bionic dexterous hand that combines 22 degrees of freedom with remarkable strength and finesse. It’s a hand that truly understands precision. It can lift 30 kilograms, yet is delicate enough to thread a needle.Each finger can bear 1.5 kilograms, and the entire hand can gently hold a piece of tofu or sense the subtle expansion of a balloon. Powered by a tendon-driven mechanism with integrated actuators inside the forearm, it achieves compact design and natural, human-like movement. From precision assembly and component handling to material transport and human-robot collaboration,the PANTHEON HAND 22 shows what it means for humanoid robots to truly work with their hands.

Hands are as important as the brain. From Shenzhen, Stella Robot has unveiled the PANTHEON HAND 22:a new generation of bionic dexterous hand that combines 22 degrees of freedom with remarkable strength and finesse. It’s a hand that truly understands precision. It can lift 30 kilograms, yet is delicate enough to thread a needle.Each finger can bear 1.5 kilograms, and the entire hand can gently hold a piece of tofu or sense the subtle expansion of a balloon. Powered by a tendon-driven mechanism with integrated actuators inside the forearm, it achieves compact design and natural, human-like movement. From precision assembly and component handling to material transport and human-robot collaboration,the PANTHEON HAND 22 shows what it means for humanoid robots to truly work with their hands.

CyberRobo

26,846 görüntüleme • 7 ay önce

Collecting data is a PAAAAAAAIN❗ If only there were a solution out there... (𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 😱) Jannik Grothusen, researchers and founder in stealth mode 👀 from TU Munich, has created a new tool that helps collect data for robots to learn how to perform tasks. It’s inspired by a device from Stanford, but it’s even better! Here’s why: ✅ It can collect and process data in real-time, meaning no delays. ✅ It’s super easy to control, so collecting data is much faster and simpler. ✅ It can be used with different robot parts because of its smart, modular design. Best of all, this amazing tool is 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲, so anyone can use it or improve it! Github: The system is inspired by Cheng Chi; Universal Manipulation Interface (UMI). Credit: Jannik Grothusen

Collecting data is a PAAAAAAAIN❗ If only there were a solution out there... (𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 😱) Jannik Grothusen, researchers and founder in stealth mode 👀 from TU Munich, has created a new tool that helps collect data for robots to learn how to perform tasks. It’s inspired by a device from Stanford, but it’s even better! Here’s why: ✅ It can collect and process data in real-time, meaning no delays. ✅ It’s super easy to control, so collecting data is much faster and simpler. ✅ It can be used with different robot parts because of its smart, modular design. Best of all, this amazing tool is 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲, so anyone can use it or improve it! Github: The system is inspired by Cheng Chi; Universal Manipulation Interface (UMI). Credit: Jannik Grothusen

Ilir Aliu

47,397 görüntüleme • 1 yıl önce

Teaching robots real dexterity has always been a challenge. But what if they could handle tools like a human? DexterityGen (DexGen) is a new system that helps robots use their hands better. It improves how they grip, move, and handle objects… from holding a pen to using a screwdriver. DexGen learns in simulation and refines its skills in the real world, making robotic hands much more useful. What makes DexGen special? ✅ Smarter movements that refine rough actions into precise skills ✅ Trained on a massive collection of dexterous tasks for better learning ✅ Better teleoperation that makes robotic hand control easier and safer ✅ Handles real-world challenges like small objects, tricky angles, and gravity This moves robots closer to real dexterity. It makes tool use more natural, improves stability, and brings robotic hands one step closer to human-level skill. Seen at Zhao-Heng Yin 🫶 Github: Paper:

Teaching robots real dexterity has always been a challenge. But what if they could handle tools like a human? DexterityGen (DexGen) is a new system that helps robots use their hands better. It improves how they grip, move, and handle objects… from holding a pen to using a screwdriver. DexGen learns in simulation and refines its skills in the real world, making robotic hands much more useful. What makes DexGen special? ✅ Smarter movements that refine rough actions into precise skills ✅ Trained on a massive collection of dexterous tasks for better learning ✅ Better teleoperation that makes robotic hand control easier and safer ✅ Handles real-world challenges like small objects, tricky angles, and gravity This moves robots closer to real dexterity. It makes tool use more natural, improves stability, and brings robotic hands one step closer to human-level skill. Seen at Zhao-Heng Yin 🫶 Github: Paper:

Ilir Aliu

51,490 görüntüleme • 1 yıl önce

New Gemini Robotics 1.5 models will enable robots to better reason, plan ahead, use digital tools like Search, and transfer learning from one kind of robot to another. Our next big step towards general-purpose robots that are truly helpful — you can see how the robot reasons as it sorts laundry in the video below.

New Gemini Robotics 1.5 models will enable robots to better reason, plan ahead, use digital tools like Search, and transfer learning from one kind of robot to another. Our next big step towards general-purpose robots that are truly helpful — you can see how the robot reasons as it sorts laundry in the video below.

Sundar Pichai

496,038 görüntüleme • 8 ay önce

🇨🇳 It has started. A new home service in China pairs human cleaners with autonomous AI robots to tackle household chores. Residents in Shenzhen can now book a service where a human professional and an autonomous robot arrive together to clean their home. Real houses present a chaotic mess of dropped toys and random furniture that confuse traditional machines. X Square Robot and a major service platform named 58[.]com decided to tackle this chaos by launching China's first robot cleaner service in March-26. Customers use an application to hire a cleaning crew that consists of 1 human worker and 1 robot. The human takes care of the tricky chores that require complex judgment. The robot handles the repetitive physical work like picking up trash and wiping down flat surfaces. This machine runs on a system called WALL-A, which acts as a single continuous AI brain rather than a list of pre-written rules. They built this AI foundation model to perceive its surroundings and make its own decisions without human guidance. It processes visual data and plans multi-step actions. And deploying these robots into actual homes now provides the massive amounts of extremely important training data to improve it continuously. Alibaba and ByteDance backed this project. IMO, if the foundational model behind it figures out how to navigate a messy living room without getting stuck, it can learn to operate in almost any other physical environment.

🇨🇳 It has started. A new home service in China pairs human cleaners with autonomous AI robots to tackle household chores. Residents in Shenzhen can now book a service where a human professional and an autonomous robot arrive together to clean their home. Real houses present a chaotic mess of dropped toys and random furniture that confuse traditional machines. X Square Robot and a major service platform named 58[.]com decided to tackle this chaos by launching China's first robot cleaner service in March-26. Customers use an application to hire a cleaning crew that consists of 1 human worker and 1 robot. The human takes care of the tricky chores that require complex judgment. The robot handles the repetitive physical work like picking up trash and wiping down flat surfaces. This machine runs on a system called WALL-A, which acts as a single continuous AI brain rather than a list of pre-written rules. They built this AI foundation model to perceive its surroundings and make its own decisions without human guidance. It processes visual data and plans multi-step actions. And deploying these robots into actual homes now provides the massive amounts of extremely important training data to improve it continuously. Alibaba and ByteDance backed this project. IMO, if the foundational model behind it figures out how to navigate a messy living room without getting stuck, it can learn to operate in almost any other physical environment.

Rohan Paul

52,925 görüntüleme • 2 ay önce