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Precision robots for electronics and lab automation! 🧪 Mecademic makes robots that do two things simultaneously, manipulate material and move it. They're not competing with the big legacy robot manufacturers. They're smaller, more nimble, and obsessively precise. Their niche? Electronics manufacturing and lab automation. Why? Repeatability and precision. 5...

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Lukas Ziegler

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16,348 views • 4 months ago •via X (Twitter)

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Welcome to the pico world! 🔬 Micro-dispensing at the picoliter scale is incredible when you compare it to everyday numbers: a single raindrop is about 50 microliters, roughly 50 million times larger than a picoliter. Being able to place droplets this small without touching the surface is key for biotech, diagnostics, and micro-electronics, where tiny volumes matter. And at this scale, two basics become critical: → Accuracy = how close you are to the real value. → Precision = how repeatable each droplet is. I could watch it all day long! 🤯 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

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Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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21,042 views • 9 months ago

Robotics is entering the mainstream! 👀 Let's accept this fact. Consumptionism – stonks. Possibilities (HW + SW) – stonks. Demographics - not stonks. Modern robots are often designed to interact with our legacy world, whether it's a household, a factory, or a shipyard. That means they often need to work with existing machines, tools, and spaces. In short: retrofitting. Improving old machines with new technologies without major interference in their operation. Modern way of integrating things. You don't have to change the entire environment to deploy a robot. The robot will adapt, just as human would when freshly hired. The promise is to have an army of robots to help with the world designed for us. I also believe that general purpose robots, are not a direct competition for single purpose machines (like a highly efficient specialized packaging machine, for example). It's like adding a robot to this carriage. Specialized machine could be a car ;) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Robotics is entering the mainstream! 👀 Let's accept this fact. Consumptionism – stonks. Possibilities (HW + SW) – stonks. Demographics - not stonks. Modern robots are often designed to interact with our legacy world, whether it's a household, a factory, or a shipyard. That means they often need to work with existing machines, tools, and spaces. In short: retrofitting. Improving old machines with new technologies without major interference in their operation. Modern way of integrating things. You don't have to change the entire environment to deploy a robot. The robot will adapt, just as human would when freshly hired. The promise is to have an army of robots to help with the world designed for us. I also believe that general purpose robots, are not a direct competition for single purpose machines (like a highly efficient specialized packaging machine, for example). It's like adding a robot to this carriage. Specialized machine could be a car ;) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

14,396 views • 9 months ago

A lot of hype around giving robots touch. That's the OG tactile sensing. FORCE. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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A lot of hype around giving robots touch. That's the OG tactile sensing. FORCE. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

216,986 views • 5 months ago

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! 🙏
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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! 🙏

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46,285 views • 1 year ago

Humanoid robots that can barely walk after 10 years of development, and grab a cup after 7th attempt. Meanwhile: specialized robots that have been dominating their specific task since 2008. That's one of the worst tasks to do! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Humanoid robots that can barely walk after 10 years of development, and grab a cup after 7th attempt. Meanwhile: specialized robots that have been dominating their specific task since 2008. That's one of the worst tasks to do! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

51,527 views • 4 months ago

🚀 🔥 AgiBot deploys Real-World Reinforcement Learning (RW-RL) in industrial robotics with Longcheer Technology. Robots now learn new skills in tens of MINUTES (not weeks), adapt to variations autonomously, and reconfigure flexibly, solving rigid automation pain points in precision manufacturing. A giant leap of intelligent automation for precision manufacturing! #AgiBot #ReinforcementLearning #RealWorldRL #Robotics #AI #IndustrialRobotics
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🚀 🔥 AgiBot deploys Real-World Reinforcement Learning (RW-RL) in industrial robotics with Longcheer Technology. Robots now learn new skills in tens of MINUTES (not weeks), adapt to variations autonomously, and reconfigure flexibly, solving rigid automation pain points in precision manufacturing. A giant leap of intelligent automation for precision manufacturing! #AgiBot #ReinforcementLearning #RealWorldRL #Robotics #AI #IndustrialRobotics

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131,958 views • 1 year ago

Modern manufacturing robots are far more precise than they look. A six-axis industrial robot can move a tool through several metres of space and repeatedly bring it back to within a few hundredths of a millimetre. Some precision oriented systems achieve repeatability of around 0.02-0.05 mm. That precision is one reason mass manufacturing looks the way it does today. A car body can move through a factory floor while robots weld the same points, drill the same holes and paint complex surfaces with almost identical movements, thousands of times over. The first industrial robots entered factories in the early 1960s, mostly doing repetitive and dangerous work. Sixty years later, they can repeat precise movements thousands of times with a consistency that humans simply cannot maintain at industrial scale.
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Modern manufacturing robots are far more precise than they look. A six-axis industrial robot can move a tool through several metres of space and repeatedly bring it back to within a few hundredths of a millimetre. Some precision oriented systems achieve repeatability of around 0.02-0.05 mm. That precision is one reason mass manufacturing looks the way it does today. A car body can move through a factory floor while robots weld the same points, drill the same holes and paint complex surfaces with almost identical movements, thousands of times over. The first industrial robots entered factories in the early 1960s, mostly doing repetitive and dangerous work. Sixty years later, they can repeat precise movements thousands of times with a consistency that humans simply cannot maintain at industrial scale.

Ammanichanda

173,361 views • 1 month ago

Seat assembling robots! 💺 This robot from KUKA performs an incredibly technology-heavy process. 🦺 It assembles the seats in the car. And it's so hard? Well, when the car moves along with the production line, things get more complicated. The robot also moves on a special additional axis, so it synchronizes with the production line. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Seat assembling robots! 💺 This robot from KUKA performs an incredibly technology-heavy process. 🦺 It assembles the seats in the car. And it's so hard? Well, when the car moves along with the production line, things get more complicated. The robot also moves on a special additional axis, so it synchronizes with the production line. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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10,554 views • 11 months ago

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Robots moving railcars! 🚃 Did you know that KUKA is also in the mobile robots business? Yes, you heard that right. And not just any robots. Robots that carry up to 56 tons! 🏋🏼 The railcar production process is highly complex, particularly when moving massive cars sideways within a plant. This challenge has been addressed at the Siemens facility in Germany using the OmniMove system from KUKA. The system allows for precise positioning, enabling the units to lift, move, and lower railcars with remarkable accuracy. With Mecanum wheels, the OmniMove units can move seamlessly in any direction, making the process incredibly efficient. Together, these units are capable of lifting up to 56 tons, streamlining heavy railcar production. This one is clearly tele-operated, but just looking at it makes me feel safer when I see a human in the loop. What a great use case for mobile robots! 😮‍💨 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

19,285 views • 4 months ago