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Lukas Ziegler

@lukas_m_ziegler • 60,348 subscribers

robotics evangelist | riding the wave of robotics | angel investing 🕵🏼‍♂️

Shorts

Nature-inspired gripper! 🦎 A chameleon doesn't grab its prey, but its tongue wraps around it. Festo built a gripper that does the same thing, and the mechanism is more elegant than it looks. The FlexShapeGripper is an elastic silicone cap sitting on a water-filled chamber. It works as a double-acting cylinder, one chamber holds compressed air, the other is permanently filled with water. Vent the air chamber, and the water-filled silicone pulls itself inwards. The cap folds over whatever is underneath and locks around its shape. The grip is form-locking, so the object's own geometry does the work of holding it. → Adapts to any shape, including delicate and irregularly shaped items where rigid jaws fail → Can pick up and deposit several objects in one operation → Pneumatic drive, minimal energy consumption → The silicone cap maps directly onto the chameleon's tongue Always good to see the mimicry developments from Festo! :) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Nature-inspired gripper! 🦎 A chameleon doesn't grab its prey, but its tongue wraps around it. Festo built a gripper that does the same thing, and the mechanism is more elegant than it looks. The FlexShapeGripper is an elastic silicone cap sitting on a water-filled chamber. It works as a double-acting cylinder, one chamber holds compressed air, the other is permanently filled with water. Vent the air chamber, and the water-filled silicone pulls itself inwards. The cap folds over whatever is underneath and locks around its shape. The grip is form-locking, so the object's own geometry does the work of holding it. → Adapts to any shape, including delicate and irregularly shaped items where rigid jaws fail → Can pick up and deposit several objects in one operation → Pneumatic drive, minimal energy consumption → The silicone cap maps directly onto the chameleon's tongue Always good to see the mimicry developments from Festo! :) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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High school students built an autonomous ball-collecting robot! 🎾 A group of high school students built a robot that picks up balls and shoots them into a bin while moving without stopping, with impressive speed and accuracy. It combines mechanical design, sensors, and software making constant adjustments in real time while the robot is driving. When teenagers can build systems this sophisticated, the talent pipeline for the robotics industry is accelerating! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

High school students built an autonomous ball-collecting robot! 🎾 A group of high school students built a robot that picks up balls and shoots them into a bin while moving without stopping, with impressive speed and accuracy. It combines mechanical design, sensors, and software making constant adjustments in real time while the robot is driving. When teenagers can build systems this sophisticated, the talent pipeline for the robotics industry is accelerating! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

1,200,374 просмотров

A metal origami! 🪭 This method is called Hyperbolic Metal Forming and is hypnotizing to watch. Instead of shaping metal with slow mechanical force, HMF uses controlled shockwaves to form complex geometries at extreme speed, often without the need for heavy dies or post-processing. The result is stronger, lighter parts with shapes that are almost impossible using traditional stamping. That’s why you see it popping up in aerospace, automotive structures, and defense components. Think of it like metal origami, but driven by high-energy pulses instead of presses. A small reminder that some things in manufacturing come from physics, not just automation. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

A metal origami! 🪭 This method is called Hyperbolic Metal Forming and is hypnotizing to watch. Instead of shaping metal with slow mechanical force, HMF uses controlled shockwaves to form complex geometries at extreme speed, often without the need for heavy dies or post-processing. The result is stronger, lighter parts with shapes that are almost impossible using traditional stamping. That’s why you see it popping up in aerospace, automotive structures, and defense components. Think of it like metal origami, but driven by high-energy pulses instead of presses. A small reminder that some things in manufacturing come from physics, not just automation. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

567,473 просмотров

'should we get an uber?' 'naah, it's walking distance' we all have that one friend who says.. btw. cool stuff from RIVR showing how deliveries of the future might look like

'should we get an uber?' 'naah, it's walking distance' we all have that one friend who says.. btw. cool stuff from RIVR showing how deliveries of the future might look like

428,523 просмотров

Sub-40ms full self-driving on a $100 drone! 🚁 A demonstration showing a complete full-self-driving pipeline running in under 40 milliseconds on a $100 drone. The prompt: "Find the bike and land." No pre-mapping. Running real-time on commodity hardware. For context, human reaction time is around 200-250ms. This drone is processing sensor data, understanding natural language commands, identifying objects, planning motion, and executing control, all in 40ms. This is what happens when foundation models meet efficient inference. The models get smaller and faster while maintaining capability. The hardware gets cheaper while getting more powerful. The intersection makes previously impossible applications suddenly viable. A few years ago, this required thousands of dollars in compute, pre-mapped environments, and cloud connectivity. Now it runs locally on hardware that costs less than a nice dinner. Awesome stuff Chester & ! 😮‍💨 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Sub-40ms full self-driving on a $100 drone! 🚁 A demonstration showing a complete full-self-driving pipeline running in under 40 milliseconds on a $100 drone. The prompt: "Find the bike and land." No pre-mapping. Running real-time on commodity hardware. For context, human reaction time is around 200-250ms. This drone is processing sensor data, understanding natural language commands, identifying objects, planning motion, and executing control, all in 40ms. This is what happens when foundation models meet efficient inference. The models get smaller and faster while maintaining capability. The hardware gets cheaper while getting more powerful. The intersection makes previously impossible applications suddenly viable. A few years ago, this required thousands of dollars in compute, pre-mapped environments, and cloud connectivity. Now it runs locally on hardware that costs less than a nice dinner. Awesome stuff Chester & ! 😮‍💨 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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3D printing houses will be (is) a HUGE use case for robots robots building shelters go brrr

3D printing houses will be (is) a HUGE use case for robots robots building shelters go brrr

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🚨 BREAKING: Walden Robotics has just come out of stealth with $300 million in funding and a $1.1 billion valuation. Another unicorn in the robotics space. 🦄 Just 6 months after incubation. The company was spun out of Toyota's robotics research lab by co-founder Russ Tedrake, a former Toyota Research Institute executive and MIT professor who taught a course on robotic legs. The seed round was co-led by Deviation Capital and Toyota, with participation from: NVIDIA, Boeing, Samsung Ventures, CoreWeave Ventures and AE Ventures. The robot is already working. A pilot is live at a North American Toyota factory where a Walden humanoid is pulling eight-hour shifts alongside human workers, loading and unloading car parts, cleaning machinery, kitting for assembly. A shift. Every day. Walden builds its own hardware, software and AI models, designed to continuously learn and improve in real production environments. Tedrake's words on the opportunity are worth noting: "Everyone recognises the magnitude of the opportunity and the technology feels ready, but success is not assured. You have to think through the business case, the unit economics, and how to marry the best of manufacturing and logistics with disruptive AI technology." Rare honesty in a space full of hype. The race to own that market is accelerating every single week. 🤖 Great story by Bloomberg here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

🚨 BREAKING: Walden Robotics has just come out of stealth with $300 million in funding and a $1.1 billion valuation. Another unicorn in the robotics space. 🦄 Just 6 months after incubation. The company was spun out of Toyota's robotics research lab by co-founder Russ Tedrake, a former Toyota Research Institute executive and MIT professor who taught a course on robotic legs. The seed round was co-led by Deviation Capital and Toyota, with participation from: NVIDIA, Boeing, Samsung Ventures, CoreWeave Ventures and AE Ventures. The robot is already working. A pilot is live at a North American Toyota factory where a Walden humanoid is pulling eight-hour shifts alongside human workers, loading and unloading car parts, cleaning machinery, kitting for assembly. A shift. Every day. Walden builds its own hardware, software and AI models, designed to continuously learn and improve in real production environments. Tedrake's words on the opportunity are worth noting: "Everyone recognises the magnitude of the opportunity and the technology feels ready, but success is not assured. You have to think through the business case, the unit economics, and how to marry the best of manufacturing and logistics with disruptive AI technology." Rare honesty in a space full of hype. The race to own that market is accelerating every single week. 🤖 Great story by Bloomberg here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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Spiders as robotic grippers? 🕷️ Researchers made a stunning discovery at Rice University. Dead spiders are being used as mechanical grippers. Yes, they use dead spiders as grippers... But how? 👀 It turns out that spiders use hydraulics to move their legs. They extend their legs by contracting their prosoma chamber, which sends fluid into their bodies. Scientists selected wolf spiders that can lift 130% of their weight. Using such a solution could be useful for pick-and-place processes in electronics assembly, for instance. Their discovery might start the field of necrobotics. Given my arachnophobia, I'm not sure how I'd react to such a grip. 🕸️ ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Spiders as robotic grippers? 🕷️ Researchers made a stunning discovery at Rice University. Dead spiders are being used as mechanical grippers. Yes, they use dead spiders as grippers... But how? 👀 It turns out that spiders use hydraulics to move their legs. They extend their legs by contracting their prosoma chamber, which sends fluid into their bodies. Scientists selected wolf spiders that can lift 130% of their weight. Using such a solution could be useful for pick-and-place processes in electronics assembly, for instance. Their discovery might start the field of necrobotics. Given my arachnophobia, I'm not sure how I'd react to such a grip. 🕸️ ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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AI that watches your work! 👀 Codya built AI that watches assembly lines and verifies every step got done right. Engine being assembled, bolt by bolt. The model tracks each one, inserted vs fastened. Standard computer vision would struggle here. It's about occlusion. A worker's hands constantly cover the bolts during assembly. Hand moves in, bolt disappears. Hand moves away, bolt reappears. Without smart tracking, the model forgets which bolt is which every time it's hidden. They solved it with BoT-SORT, a tracking algorithm that keeps object identity through occlusions. When a hand covers a bolt and moves away, the tracker knows it's still the same bolt, same state, same position. SkalskiP looking forward to see more and more industrial use cases with your Roboflow models :) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

AI that watches your work! 👀 Codya built AI that watches assembly lines and verifies every step got done right. Engine being assembled, bolt by bolt. The model tracks each one, inserted vs fastened. Standard computer vision would struggle here. It's about occlusion. A worker's hands constantly cover the bolts during assembly. Hand moves in, bolt disappears. Hand moves away, bolt reappears. Without smart tracking, the model forgets which bolt is which every time it's hidden. They solved it with BoT-SORT, a tracking algorithm that keeps object identity through occlusions. When a hand covers a bolt and moves away, the tracker knows it's still the same bolt, same state, same position. SkalskiP looking forward to see more and more industrial use cases with your Roboflow models :) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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That’s insane! 🤯 A student built an acoustic levitation divide with an Arduino board. He built it using an Arduino Nano, a motor driver, and 60 ultrasonic transducers that can levitate low-density objects in place indefinitely. The transducers send out 40 kHz waves that create standing waves. The interference pattern produces nulls that trap objects. High-pressure areas form below and above the object, locking it in the low-pressure area between them. The transducers produce two sound waves moving in opposing directions at the same frequency and amplitude. The effect is that the low-pressure areas don't appear to move, like whipping a rope from both ends and having the wave meet in the middle. Sound waves are oscillating at high and low pressures. By creating a sound wave that doesn't move forward (a standing wave), you create areas of constant pressure. 🔉 Objects get trapped in the null points between high-pressure zones. The craziest part is that this was made more than 7 years ago! DIY levitation 😮‍💨 Reddit link: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

That’s insane! 🤯 A student built an acoustic levitation divide with an Arduino board. He built it using an Arduino Nano, a motor driver, and 60 ultrasonic transducers that can levitate low-density objects in place indefinitely. The transducers send out 40 kHz waves that create standing waves. The interference pattern produces nulls that trap objects. High-pressure areas form below and above the object, locking it in the low-pressure area between them. The transducers produce two sound waves moving in opposing directions at the same frequency and amplitude. The effect is that the low-pressure areas don't appear to move, like whipping a rope from both ends and having the wave meet in the middle. Sound waves are oscillating at high and low pressures. By creating a sound wave that doesn't move forward (a standing wave), you create areas of constant pressure. 🔉 Objects get trapped in the null points between high-pressure zones. The craziest part is that this was made more than 7 years ago! DIY levitation 😮‍💨 Reddit link: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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Food automation made accessible! 🥔 During the Automate Show, Schmalz presented their configurable gripper that is a great choice for food automation. The original is FDA-approved, food-grade, handles raw meat, completely washable. Perfect for any food application. But the price tag is too expensive for a lot of applications. The new aluminum gripper is configurable and cost-effective. Not for meat, but great for produce picking and bin picking applications. Same modular approach, lower cost barrier. Opens up food automation to operations that couldn't justify the premium version. Working with ABB Robotics delta robots, the system handles the speed and precision food processors need, plus the flexibility to swap grippers for different applications. Be prepared to be flooded with Automate content! 🤠🇺🇸 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Food automation made accessible! 🥔 During the Automate Show, Schmalz presented their configurable gripper that is a great choice for food automation. The original is FDA-approved, food-grade, handles raw meat, completely washable. Perfect for any food application. But the price tag is too expensive for a lot of applications. The new aluminum gripper is configurable and cost-effective. Not for meat, but great for produce picking and bin picking applications. Same modular approach, lower cost barrier. Opens up food automation to operations that couldn't justify the premium version. Working with ABB Robotics delta robots, the system handles the speed and precision food processors need, plus the flexibility to swap grippers for different applications. Be prepared to be flooded with Automate content! 🤠🇺🇸 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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A robot mower on steroids! 💉 This mowing robot can handle any bush. Literally. It's well-suited for work on PV farms, which are usually in remote areas and typically don't have permanent staff. I don't even need to mention the origin country. Chinese are cooking. This type of use case makes a lot of sense for robots. Someone mentioned that it's AI generated so, here's the OEM page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

A robot mower on steroids! 💉 This mowing robot can handle any bush. Literally. It's well-suited for work on PV farms, which are usually in remote areas and typically don't have permanent staff. I don't even need to mention the origin country. Chinese are cooking. This type of use case makes a lot of sense for robots. Someone mentioned that it's AI generated so, here's the OEM page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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When robots take the night shift shopping spree! 🛍️ Robots navigate through dm-drogerie markt Deutschland stores at night to create a digital replica of the store's layout, known as a "digital twin." Developed Ubica Robotics GmbH, these autonomous robots scan shelves to provide real-time information about item positions, pricing, stock gaps, and store layouts. 🏪 This data serves multiple purposes, such as improving staff routes, enhancing inventory management, and informing the creation of planograms for more efficient store layouts. It combines digital twin with robotics and it's really cool use case. What are your thoughts?

When robots take the night shift shopping spree! 🛍️ Robots navigate through dm-drogerie markt Deutschland stores at night to create a digital replica of the store's layout, known as a "digital twin." Developed Ubica Robotics GmbH, these autonomous robots scan shelves to provide real-time information about item positions, pricing, stock gaps, and store layouts. 🏪 This data serves multiple purposes, such as improving staff routes, enhancing inventory management, and informing the creation of planograms for more efficient store layouts. It combines digital twin with robotics and it's really cool use case. What are your thoughts?

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High-speed labeling is harder than it looks! 🍼 I remember when I was programming robots myself and the struggle of making an application really repeatable. It was hard. Super hard. That's why seeing a machine working as smooth as here, it's incredible! 🤯 Applying shrink sleeves without wrinkles or misalignment becomes a real bottleneck at scale. Krones machine solves that by combining fast application with precise servo-controlled cutting. It can handle up to 50,000 containers per hour, keep labels perfectly aligned, and switch between bottle shapes with minimal downtime. For manufacturers, that reliability matters. Magic!!! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

High-speed labeling is harder than it looks! 🍼 I remember when I was programming robots myself and the struggle of making an application really repeatable. It was hard. Super hard. That's why seeing a machine working as smooth as here, it's incredible! 🤯 Applying shrink sleeves without wrinkles or misalignment becomes a real bottleneck at scale. Krones machine solves that by combining fast application with precise servo-controlled cutting. It can handle up to 50,000 containers per hour, keep labels perfectly aligned, and switch between bottle shapes with minimal downtime. For manufacturers, that reliability matters. Magic!!! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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Multi-axis 3D printing with curved layers! 🖨️ Researchers from the The University of Manchester introduced a neural network-based computational pipeline as a representation-agnostic slicer for multi-axis 3D printing. Traditional 3D printing works like stacking pancakes, flat layers on top of each other. 🥞 This often requires temporary support structures that get thrown away after printing, wastes material, and creates weaker parts. Multi-axis 3D printing can print along curved paths that follow the object's natural shape. This eliminates support structures and makes stronger parts. But figuring out these curved paths is mathematically complex, you need to avoid collisions, respect what the printer can physically do, and optimize for strength. The neural network solves this automatically. It learns to create a "field" around the object, then extracts curved printing paths from this field. Because the entire process is differentiable (translation for non-math specialists, meaning you can optimize it end-to-end), the AI can directly optimize for manufacturing goals like "no support structures needed" and "make it as strong as possible." Here's the project: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Multi-axis 3D printing with curved layers! 🖨️ Researchers from the The University of Manchester introduced a neural network-based computational pipeline as a representation-agnostic slicer for multi-axis 3D printing. Traditional 3D printing works like stacking pancakes, flat layers on top of each other. 🥞 This often requires temporary support structures that get thrown away after printing, wastes material, and creates weaker parts. Multi-axis 3D printing can print along curved paths that follow the object's natural shape. This eliminates support structures and makes stronger parts. But figuring out these curved paths is mathematically complex, you need to avoid collisions, respect what the printer can physically do, and optimize for strength. The neural network solves this automatically. It learns to create a "field" around the object, then extracts curved printing paths from this field. Because the entire process is differentiable (translation for non-math specialists, meaning you can optimize it end-to-end), the AI can directly optimize for manufacturing goals like "no support structures needed" and "make it as strong as possible." Here's the project: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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When robots take the night shift shopping spree! 🛍️ Robots navigate through dm-drogerie markt Deutschland stores at night to create a digital replica of the store's layout, known as a "digital twin." Developed Ubica Robotics GmbH, these autonomous robots scan shelves to provide real-time information about item positions, pricing, stock gaps, and store layouts. 🏪 This data serves multiple purposes, such as improving staff routes, enhancing inventory management, and informing the creation of planograms for more efficient store layouts. It combines digital twin with robotics and it's really cool use case. What are your thoughts? ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

When robots take the night shift shopping spree! 🛍️ Robots navigate through dm-drogerie markt Deutschland stores at night to create a digital replica of the store's layout, known as a "digital twin." Developed Ubica Robotics GmbH, these autonomous robots scan shelves to provide real-time information about item positions, pricing, stock gaps, and store layouts. 🏪 This data serves multiple purposes, such as improving staff routes, enhancing inventory management, and informing the creation of planograms for more efficient store layouts. It combines digital twin with robotics and it's really cool use case. What are your thoughts? ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

65,006 просмотров

Genesis AI just unveiled Eno. It's humanoid robot that challenges everything the industry assumed about what robots should look like. Forbes just called it 'the iPhone moment for humanoid robots'. No head. No face. No exposed motors or cables. 22 degrees of freedom per hand with different finger lengths (like actual human hands). Back-drivable for safety. Onboard cameras and tactile sensors. In demos: bundling wires with tape (genuinely hard, tape is sticky and unpredictable), performing lab automation with millimeter precision on unmodified equipment. Optional chest screen shows the robot's reasoning before it acts, a visual window into its mind to build trust. Powered by Genesis AI GENE foundation model. Payload 3-5kg per arm, 4-6 hours battery. Industrial deployments late 2026, homes much later. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Genesis AI just unveiled Eno. It's humanoid robot that challenges everything the industry assumed about what robots should look like. Forbes just called it 'the iPhone moment for humanoid robots'. No head. No face. No exposed motors or cables. 22 degrees of freedom per hand with different finger lengths (like actual human hands). Back-drivable for safety. Onboard cameras and tactile sensors. In demos: bundling wires with tape (genuinely hard, tape is sticky and unpredictable), performing lab automation with millimeter precision on unmodified equipment. Optional chest screen shows the robot's reasoning before it acts, a visual window into its mind to build trust. Powered by Genesis AI GENE foundation model. Payload 3-5kg per arm, 4-6 hours battery. Industrial deployments late 2026, homes much later. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

29,453 просмотров

Autonomous excavator building a wall! 🪨 This will blow your mind! 🤯 Researchers from ETH Zürich have used an autonomous excavator to build a 65-meter-long, six-meter-high dry-stone wall. The autonomous system, called "Heap," precisely scanned and placed stones, forming a wall. Through computer-aided design and control, the robot was able to handle and position over 900 individual elements, some weighing over 1000 kilograms. What about autonomous excavators? Perhaps tele-op is also an option that could let people work remotely even as an excavator operator!

Autonomous excavator building a wall! 🪨 This will blow your mind! 🤯 Researchers from ETH Zürich have used an autonomous excavator to build a 65-meter-long, six-meter-high dry-stone wall. The autonomous system, called "Heap," precisely scanned and placed stones, forming a wall. Through computer-aided design and control, the robot was able to handle and position over 900 individual elements, some weighing over 1000 kilograms. What about autonomous excavators? Perhaps tele-op is also an option that could let people work remotely even as an excavator operator!

112,372 просмотров

Autonomous excavator building a wall! 🪨 This will blow your mind! 🤯 Researchers from ETH Zürich have used an autonomous excavator to build a 65-meter-long, six-meter-high dry-stone wall. The autonomous system, called "Heap," precisely firstly scanned and then placed stones, forming a wall. Through computer-aided design and control, the robot was able to handle and position over 900 individual elements, some weighing over 1000 kilograms. What about autonomous excavators? Perhaps tele-op is also an option that could let people work remotely even as an excavator operator! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Autonomous excavator building a wall! 🪨 This will blow your mind! 🤯 Researchers from ETH Zürich have used an autonomous excavator to build a 65-meter-long, six-meter-high dry-stone wall. The autonomous system, called "Heap," precisely firstly scanned and then placed stones, forming a wall. Through computer-aided design and control, the robot was able to handle and position over 900 individual elements, some weighing over 1000 kilograms. What about autonomous excavators? Perhaps tele-op is also an option that could let people work remotely even as an excavator operator! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

57,809 просмотров

AI-Powered weed control! 🌱 The LaserWeeder machine from Carbon Robotics has captured the imagination of American farmers. This technology uses AI system to identify weeds in crops and zap them with precision thermal bursts from lasers. Bit of facts about the cool robot: → The machine can remove weeds from over 40 crops and can also be used for thinning crops. → It can operate in virtually all weather conditions, with millimeter accuracy at all times, and can work through the night thanks to its built-in lighting system. → High-resolution cameras and computer machine learning enable it to distinguish weeds from crops in milliseconds. → The LaserWeeder can replace about 70 workers on farms where manual weeding is used, and can weed up to four acres per hour. What other applications can we expect to see in the future in farming applications? Btw. I believe farming robots are A HUGE THING in robotics! 🔥 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

AI-Powered weed control! 🌱 The LaserWeeder machine from Carbon Robotics has captured the imagination of American farmers. This technology uses AI system to identify weeds in crops and zap them with precision thermal bursts from lasers. Bit of facts about the cool robot: → The machine can remove weeds from over 40 crops and can also be used for thinning crops. → It can operate in virtually all weather conditions, with millimeter accuracy at all times, and can work through the night thanks to its built-in lighting system. → High-resolution cameras and computer machine learning enable it to distinguish weeds from crops in milliseconds. → The LaserWeeder can replace about 70 workers on farms where manual weeding is used, and can weed up to four acres per hour. What other applications can we expect to see in the future in farming applications? Btw. I believe farming robots are A HUGE THING in robotics! 🔥 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

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Modular robots that repair themselves by... stealing parts! 👀 A team at Columbia University built robots made of Truss Links, stick-shaped modules with magnetic connectors at each end. Connect a few and you get a structure that can expand, contract, roll, and reshape itself. If a link breaks or comes loose, the robot grabs a spare module nearby and rebuilds itself. No human intervention needed. A tetrahedron-shaped robot grabbed a spare link like a walking stick. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Modular robots that repair themselves by... stealing parts! 👀 A team at Columbia University built robots made of Truss Links, stick-shaped modules with magnetic connectors at each end. Connect a few and you get a structure that can expand, contract, roll, and reshape itself. If a link breaks or comes loose, the robot grabs a spare module nearby and rebuilds itself. No human intervention needed. A tetrahedron-shaped robot grabbed a spare link like a walking stick. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

1,055,957 просмотров • 1 месяц назад

A flying skateboard, and it's actually shipping! 🛹 Personal eVTOLs so far have meant a seat, a cockpit and a pilot's licence. It is a platform you stand on. Four ducted propulsion units arranged in petal-like sections, eight rotors, and a self-developed flight controller called the NA80 running dual-redundant architecture with three inertial measurement units per unit. The control scheme is the part worth understanding. High-precision sensors track the combined centre of gravity of rider and machine, and adjust rotor thrust as you lean. Steering is a nudge on a control stick, takeoff is a button press. CoolFly says most people get it in about 10 minutes, roughly like learning a self-balancing scooter. What makes this more than a stunt is the paperwork around it: China's revised Civil Aviation Law took effect on 1 July giving the low-altitude economy legal standing, and in June an insurer underwrote the first policy written specifically for standing manned flying vehicles. The law and the insurance arrived before the vehicle did. 11 minutes of airtime and nowhere to sit. Would you step on? :) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

A flying skateboard, and it's actually shipping! 🛹 Personal eVTOLs so far have meant a seat, a cockpit and a pilot's licence. It is a platform you stand on. Four ducted propulsion units arranged in petal-like sections, eight rotors, and a self-developed flight controller called the NA80 running dual-redundant architecture with three inertial measurement units per unit. The control scheme is the part worth understanding. High-precision sensors track the combined centre of gravity of rider and machine, and adjust rotor thrust as you lean. Steering is a nudge on a control stick, takeoff is a button press. CoolFly says most people get it in about 10 minutes, roughly like learning a self-balancing scooter. What makes this more than a stunt is the paperwork around it: China's revised Civil Aviation Law took effect on 1 July giving the low-altitude economy legal standing, and in June an insurer underwrote the first policy written specifically for standing manned flying vehicles. The law and the insurance arrived before the vehicle did. 11 minutes of airtime and nowhere to sit. Would you step on? :) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

38,046 просмотров • 2 дней назад

A 40-year-old patent has finally been brought to life. That's the Y-zipper. A 3D-printed three-sided fastener that transitions any object from flexible to rigid and back again. The robotics application is the one that caught my attention. A quadruped robot that adjusts its leg stiffness depending on terrain, switching between rigid and flexible in real time without additional motors or complex mechanical systems. But this goes way beyond robotics. A wrist cast that loosens during the day and stiffens at night. A tent that pops into shape in 90 seconds instead of six minutes. The idea sat in a patent filing for four decades. It took 3D printing to finally make it real. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

A 40-year-old patent has finally been brought to life. That's the Y-zipper. A 3D-printed three-sided fastener that transitions any object from flexible to rigid and back again. The robotics application is the one that caught my attention. A quadruped robot that adjusts its leg stiffness depending on terrain, switching between rigid and flexible in real time without additional motors or complex mechanical systems. But this goes way beyond robotics. A wrist cast that loosens during the day and stiffens at night. A tent that pops into shape in 90 seconds instead of six minutes. The idea sat in a patent filing for four decades. It took 3D printing to finally make it real. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

1,805,759 просмотров • 3 месяцев назад

Meta just open-sourced its dexterity stack! 🪬 Most physics simulators were built for things that move through space. Walking robots, drones, cars. Contact is the part they approximate worst, and obviously dexterous manipulation is nothing but contact. Project SuperDex, from Meta Reality Labs Research, is built the other way around, a contact-first physics engine with the whole platform stacked on top of it. The cool part is that it's on GitHub. The engine runs one solver across rigid bodies, soft bodies, rods and tendons, shells and cloth, in the same model. → Non-convex collision with accurate contact force distributions, so a multi-finger grasp gets simulated rather than approximated → Tactile sensors and soft contact as first-class primitives → Numerical stability without the tight time-step limits explicit solvers force on you → Constraint-aware inverse kinematics running on the same optimization core as the forward dynamics Then the data layer. Put on a Quest 3, teleoperate the simulated hand with haptic feedback, and generate demonstration datasets without touching real hardware. They show a shape-sorting policy trained entirely in simulation and deployed zero-shot on a real robotic hand. Robot hands are getting good. Data for them isn't that fast. Meta is betting the cheapest way to collect contact-rich demonstrations is a headset people already own, pointed at a simulator instead of a game. 🔗 Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Meta just open-sourced its dexterity stack! 🪬 Most physics simulators were built for things that move through space. Walking robots, drones, cars. Contact is the part they approximate worst, and obviously dexterous manipulation is nothing but contact. Project SuperDex, from Meta Reality Labs Research, is built the other way around, a contact-first physics engine with the whole platform stacked on top of it. The cool part is that it's on GitHub. The engine runs one solver across rigid bodies, soft bodies, rods and tendons, shells and cloth, in the same model. → Non-convex collision with accurate contact force distributions, so a multi-finger grasp gets simulated rather than approximated → Tactile sensors and soft contact as first-class primitives → Numerical stability without the tight time-step limits explicit solvers force on you → Constraint-aware inverse kinematics running on the same optimization core as the forward dynamics Then the data layer. Put on a Quest 3, teleoperate the simulated hand with haptic feedback, and generate demonstration datasets without touching real hardware. They show a shape-sorting policy trained entirely in simulation and deployed zero-shot on a real robotic hand. Robot hands are getting good. Data for them isn't that fast. Meta is betting the cheapest way to collect contact-rich demonstrations is a headset people already own, pointed at a simulator instead of a game. 🔗 Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

41,086 просмотров • 5 дней назад

A system with moving transfer plates! 🍽️ Modular transfer plates that move items in any direction. These systems from Festo give factories something really cool; reconfigurable motion that adapts as layouts or processes change. Because they can route items in multiple directions, you can run inspections, branch flows based on sensor data, or perform operations directly on the moving parts. It could even power fully automated storage: shelves that reposition items based on real-time demand. I'd love to see more of them in 3PL centers. Where would you use them? 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

A system with moving transfer plates! 🍽️ Modular transfer plates that move items in any direction. These systems from Festo give factories something really cool; reconfigurable motion that adapts as layouts or processes change. Because they can route items in multiple directions, you can run inspections, branch flows based on sensor data, or perform operations directly on the moving parts. It could even power fully automated storage: shelves that reposition items based on real-time demand. I'd love to see more of them in 3PL centers. Where would you use them? 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

215,213 просмотров • 1 месяц назад

Trained a humanoid entirely in a 3D scan of the office. Zero real-world fine-tuning. It just walked in and worked. RL needs hundreds of thousands of attempts, and real robots can't afford to crash. A misjudged gap or a glass door collision breaks hardware and costs hours resetting. So you train in a sim. But sim policies usually train on randomized, untextured geometry; depth is easy to fake. The robot learns structure, not the real world: no materials, no lighting, no idea what anything actually is. RGB cameras carry all of that but training RGB policies in generic fake worlds won’t generalize to the real world. Niantic Spatial 🌎 Scaniverse reconstructs your scan of the real deployment site. One 360° camera walkthrough → photorealistic 3D Gaussian splat at metric scale → collision mesh pulled from the same reconstruction, so vision and physics match exactly. Drops straight into NVIDIA Isaac Sim/Lab, no manual conversion. Flexion simulation-first approach then seamlessly enables the training of RGB-only nav policies inside that reconstruction. With added domain randomization + large image encoders for robustness, this deploys straight to hardware. No real-world fine-tuning. Deployment: months of on-site adaptation → days. Tune into the NVIDIA livestream on 12 August to hear how these companies are closing the sim2real gap: NVIDIA Robotics ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Trained a humanoid entirely in a 3D scan of the office. Zero real-world fine-tuning. It just walked in and worked. RL needs hundreds of thousands of attempts, and real robots can't afford to crash. A misjudged gap or a glass door collision breaks hardware and costs hours resetting. So you train in a sim. But sim policies usually train on randomized, untextured geometry; depth is easy to fake. The robot learns structure, not the real world: no materials, no lighting, no idea what anything actually is. RGB cameras carry all of that but training RGB policies in generic fake worlds won’t generalize to the real world. Niantic Spatial 🌎 Scaniverse reconstructs your scan of the real deployment site. One 360° camera walkthrough → photorealistic 3D Gaussian splat at metric scale → collision mesh pulled from the same reconstruction, so vision and physics match exactly. Drops straight into NVIDIA Isaac Sim/Lab, no manual conversion. Flexion simulation-first approach then seamlessly enables the training of RGB-only nav policies inside that reconstruction. With added domain randomization + large image encoders for robustness, this deploys straight to hardware. No real-world fine-tuning. Deployment: months of on-site adaptation → days. Tune into the NVIDIA livestream on 12 August to hear how these companies are closing the sim2real gap: NVIDIA Robotics ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

119,163 просмотров • 23 дней назад

start building hexapods in your 20s, go into debt if you have to

start building hexapods in your 20s, go into debt if you have to

152,499 просмотров • 1 месяц назад

This is not a 2050 warehouse. This is a modern air hub of Amazon. Amazon uses robots to help sort and ship billions of packages each year. At Amazon Air, the company's main air hub in Kentucky, hundreds of self-charging robots zoom across the warehouse floor to organize orders. These robots, called “drives,” follow small stickers on the floor to know where to go and when to speed up or slow down. Amazon has more than ONE MILLION robots in its facilities, and it’s even deploying more new types of robots that can sort items of different shapes and sizes. P.S. Can you guess how many robots they had back in 2013? ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

This is not a 2050 warehouse. This is a modern air hub of Amazon. Amazon uses robots to help sort and ship billions of packages each year. At Amazon Air, the company's main air hub in Kentucky, hundreds of self-charging robots zoom across the warehouse floor to organize orders. These robots, called “drives,” follow small stickers on the floor to know where to go and when to speed up or slow down. Amazon has more than ONE MILLION robots in its facilities, and it’s even deploying more new types of robots that can sort items of different shapes and sizes. P.S. Can you guess how many robots they had back in 2013? ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

178,090 просмотров • 1 месяц назад

A drone or a submarine? 🫧 A student just built a drone that flies through the air and swims underwater — and it actually works. As part of his Bachelor’s project, Andrei Copaci created a 3D-printed, hybrid drone with variable pitch propellers, meaning the blades shift mid-flight to adapt between air and water. Just a laptop, a printer, and a smart idea. The drone is fully custom-coded and transitions seamlessly between flying and swimming. We're entering a new era, where curious students can prototype what once took massive funding and R&D efforts.

A drone or a submarine? 🫧 A student just built a drone that flies through the air and swims underwater — and it actually works. As part of his Bachelor’s project, Andrei Copaci created a 3D-printed, hybrid drone with variable pitch propellers, meaning the blades shift mid-flight to adapt between air and water. Just a laptop, a printer, and a smart idea. The drone is fully custom-coded and transitions seamlessly between flying and swimming. We're entering a new era, where curious students can prototype what once took massive funding and R&D efforts.

1,958,227 просмотров • 1 год назад

🚨 BREAKING: Gravis Robotics has raised $200M in the largest Series A in construction robotics history, led by SoftBank! 🔥 Spun out of ETH Zürich in 2022. Three years later, $200M and SoftBank backing. The company is bringing autonomous AI to the most physically demanding machines on earth. Excavators. Heavy construction machinery. Equipment that hasn't fundamentally changed in 50 years. 🚜 Most physical AI operates in static worlds. Self-driving cars navigate around obstacles. Warehouse robots move objects across fixed floors. Everything stays where it is. An excavator does the exact opposite. It works by intentionally crashing into the environment, breaking apart soil with hidden rocks, reshaping the earth with every single pass of the bucket. The world changes with every action the machine takes. → Gravis AI doesn't navigate a static world, it actively takes the world apart and puts it back together → Models trained on billions of cubic yards of simulated earth, from soft clay to rock-filled soil → Generalises across different machine manufacturers — not locked to a single platform → Brings factory-floor precision to historically unpredictable civil jobsites The macro case is overwhelming. Energy networks, data centres, housing, transit, climate infrastructure, all of it requires construction at a scale the existing workforce cannot deliver. Construction is the primary bottleneck of the entire physical AI economy. The same AI boom driving demand for data centres is now funding the robots that will build them. Europe keeps producing world-class deep tech. 🇨🇭🇪🇺 To the team behind this, MASSIVE CONGRATS! Can't wait to publish what we have created onsite with Gravis team! 🫶🏼 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

🚨 BREAKING: Gravis Robotics has raised $200M in the largest Series A in construction robotics history, led by SoftBank! 🔥 Spun out of ETH Zürich in 2022. Three years later, $200M and SoftBank backing. The company is bringing autonomous AI to the most physically demanding machines on earth. Excavators. Heavy construction machinery. Equipment that hasn't fundamentally changed in 50 years. 🚜 Most physical AI operates in static worlds. Self-driving cars navigate around obstacles. Warehouse robots move objects across fixed floors. Everything stays where it is. An excavator does the exact opposite. It works by intentionally crashing into the environment, breaking apart soil with hidden rocks, reshaping the earth with every single pass of the bucket. The world changes with every action the machine takes. → Gravis AI doesn't navigate a static world, it actively takes the world apart and puts it back together → Models trained on billions of cubic yards of simulated earth, from soft clay to rock-filled soil → Generalises across different machine manufacturers — not locked to a single platform → Brings factory-floor precision to historically unpredictable civil jobsites The macro case is overwhelming. Energy networks, data centres, housing, transit, climate infrastructure, all of it requires construction at a scale the existing workforce cannot deliver. Construction is the primary bottleneck of the entire physical AI economy. The same AI boom driving demand for data centres is now funding the robots that will build them. Europe keeps producing world-class deep tech. 🇨🇭🇪🇺 To the team behind this, MASSIVE CONGRATS! Can't wait to publish what we have created onsite with Gravis team! 🫶🏼 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

72,774 просмотров • 15 дней назад

Seeing touch without pressing down! 🫆 Most tactile sensors rely on deformation. Press down, deform the sensor, measure the deformation. But light contact, touching water, cream, soft films, doesn't deform anything. The sensor sees nothing. LightTact flips the approach. It uses optical detection instead. An ambient-blocking configuration suppresses external light and internal illumination everywhere except at actual contact points. Only scattered light from true contact gets through. The results? High-contrast raw images. Non-contact pixels stay near-black. Contact pixels show the natural appearance of whatever's touching. This works across material properties, contact forces, surface colors, and lighting conditions. Water, facial cream, thin films, liquids, all become visible the moment they touch. The sensor outputs spatially aligned visual-tactile images. Vision-language models can read them directly. Here's the paper: Changyi Lin and team - hats off ;) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Seeing touch without pressing down! 🫆 Most tactile sensors rely on deformation. Press down, deform the sensor, measure the deformation. But light contact, touching water, cream, soft films, doesn't deform anything. The sensor sees nothing. LightTact flips the approach. It uses optical detection instead. An ambient-blocking configuration suppresses external light and internal illumination everywhere except at actual contact points. Only scattered light from true contact gets through. The results? High-contrast raw images. Non-contact pixels stay near-black. Contact pixels show the natural appearance of whatever's touching. This works across material properties, contact forces, surface colors, and lighting conditions. Water, facial cream, thin films, liquids, all become visible the moment they touch. The sensor outputs spatially aligned visual-tactile images. Vision-language models can read them directly. Here's the paper: Changyi Lin and team - hats off ;) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

207,776 просмотров • 1 месяц назад

Spiderman's stuntman is a robot! 🕸️ The Walt Disney Company Imagineers designed an advanced robotics figure that flies 25 meters in the air making its own real-time decisions as it tucks, somersaults, slows down, and climbs. 🤹🏼‍♀️ The result is Spider-Man in Avengers Campus, flying above with gravity-defying feats never before seen in a Disney park. That's incredible to see how robotics is changing different verticals! That's pure magic to me! 🔮 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Spiderman's stuntman is a robot! 🕸️ The Walt Disney Company Imagineers designed an advanced robotics figure that flies 25 meters in the air making its own real-time decisions as it tucks, somersaults, slows down, and climbs. 🤹🏼‍♀️ The result is Spider-Man in Avengers Campus, flying above with gravity-defying feats never before seen in a Disney park. That's incredible to see how robotics is changing different verticals! That's pure magic to me! 🔮 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

799,927 просмотров • 8 месяцев назад

that's what I mean if I say 'go niche' in robotics mushrooms, be ready, robots are coming for ya! 🍄

that's what I mean if I say 'go niche' in robotics mushrooms, be ready, robots are coming for ya! 🍄

89,328 просмотров • 28 дней назад

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 →

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 →

773,456 просмотров • 8 месяцев назад

China is crazy. 🤯 Forget a classical grippers, and welcome to era of humanoid acting as EOATs. Someone thinking about the gripper, actually said: you know what, let's just stick half a humanoid in there and that'll solve the problem. Humanoid torso from LimX Dynamics mounted on a 6-axis industrial robot arm wasn't on my 2026 bingo, but I'll take it. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

China is crazy. 🤯 Forget a classical grippers, and welcome to era of humanoid acting as EOATs. Someone thinking about the gripper, actually said: you know what, let's just stick half a humanoid in there and that'll solve the problem. Humanoid torso from LimX Dynamics mounted on a 6-axis industrial robot arm wasn't on my 2026 bingo, but I'll take it. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

98,421 просмотров • 1 месяц назад

This drone becomes a flying manipulator! 🥏 Researchers at the The University of Tokyo developed this aerial robot. Built with four pairs of ducted fans linked by actuated joints, Dragon can reshape itself mid-flight. This allows it to grasp objects and perform tasks typically reserved for ground-based manipulators. Each segment has dual rotors, and its navigation stack calculates the most efficient shape for each object. Total payload? More than 3 kilograms. P.S. To increase Dragon's battery life, they consider allowing it to walk on the ground.

This drone becomes a flying manipulator! 🥏 Researchers at the The University of Tokyo developed this aerial robot. Built with four pairs of ducted fans linked by actuated joints, Dragon can reshape itself mid-flight. This allows it to grasp objects and perform tasks typically reserved for ground-based manipulators. Each segment has dual rotors, and its navigation stack calculates the most efficient shape for each object. Total payload? More than 3 kilograms. P.S. To increase Dragon's battery life, they consider allowing it to walk on the ground.

741,566 просмотров • 10 месяцев назад

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 →

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 →

216,986 просмотров • 3 месяцев назад

Autonomous tractor from Netherlands! 🇳🇱 Despite all the narrative, we are still building awesome companies in hardware space in Europe. Recently, I've posted about a Chinese autonomous tractors company. So today I wanted to show something that was created in the middle of Europe. This is a fully autonomous tractor from Dutch company AgXeed, designed to work on fields without any human supervision. It's powered by a diesel engine that drives a generator, which then powers electric motors driving the tracks. The fuel tank allows for 24 hours of continuous operation. (nice!) The rear hitch has an 8-ton lift capacity, the front has 3 tons. It's equipped with electric PTO, hydraulic pump, and all the connections you'd find on a traditional tractor, meaning you can attach standard farm implements. (nice! x2) Safety and navigation are handled by a LiDAR sensor on top, ultrasonic and radar sensors, and contact-sensitive bumpers. RTK GNSS receiver provides positioning accuracy down to 2.5 cm. Love seeing that so many companies are trying to make farmer's life easier! What are the others companies building in agri-tech? I want to meet them! 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Autonomous tractor from Netherlands! 🇳🇱 Despite all the narrative, we are still building awesome companies in hardware space in Europe. Recently, I've posted about a Chinese autonomous tractors company. So today I wanted to show something that was created in the middle of Europe. This is a fully autonomous tractor from Dutch company AgXeed, designed to work on fields without any human supervision. It's powered by a diesel engine that drives a generator, which then powers electric motors driving the tracks. The fuel tank allows for 24 hours of continuous operation. (nice!) The rear hitch has an 8-ton lift capacity, the front has 3 tons. It's equipped with electric PTO, hydraulic pump, and all the connections you'd find on a traditional tractor, meaning you can attach standard farm implements. (nice! x2) Safety and navigation are handled by a LiDAR sensor on top, ultrasonic and radar sensors, and contact-sensitive bumpers. RTK GNSS receiver provides positioning accuracy down to 2.5 cm. Love seeing that so many companies are trying to make farmer's life easier! What are the others companies building in agri-tech? I want to meet them! 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

170,684 просмотров • 2 месяцев назад

Open-source magnetic tactile sensor for $5! 🧲 Researchers introduced a magnetic tactile sensor that's low-cost, and easy to fabricate, democratizing tactile sensing for robotics. Operating in unstructured environments like homes and offices requires robots to sense forces during physical interaction. Yet the lack of a versatile, accessible tactile sensor has led to fragmented solutions and often force-unaware, sensorless approaches. Building an eFlesh sensor requires four components: a hobbyist 3D printer, off-the-shelf magnets (less than $5), a CAD model, and a magnetometer circuit board. The sensor is 3D printed with magnets embedded in the middle layer. Based on chosen mechanical properties, magnets displace in response to contact forces, measured by a magnetometer underneath. An open-source design tool converts simple OBJ/STL files into 3D-printable STLs. This enables application-specific sensors for robot hands, grippers, quadruped feet, and more. Slip detection generalizes to unseen objects with 95% accuracy. Visual-tactile control policies improve manipulation by 40% over vision-only baselines, achieving 90% success on precise tasks like plug insertion and credit card swiping. All design files, code, trained models, and conversion tools are openly available. Project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Open-source magnetic tactile sensor for $5! 🧲 Researchers introduced a magnetic tactile sensor that's low-cost, and easy to fabricate, democratizing tactile sensing for robotics. Operating in unstructured environments like homes and offices requires robots to sense forces during physical interaction. Yet the lack of a versatile, accessible tactile sensor has led to fragmented solutions and often force-unaware, sensorless approaches. Building an eFlesh sensor requires four components: a hobbyist 3D printer, off-the-shelf magnets (less than $5), a CAD model, and a magnetometer circuit board. The sensor is 3D printed with magnets embedded in the middle layer. Based on chosen mechanical properties, magnets displace in response to contact forces, measured by a magnetometer underneath. An open-source design tool converts simple OBJ/STL files into 3D-printable STLs. This enables application-specific sensors for robot hands, grippers, quadruped feet, and more. Slip detection generalizes to unseen objects with 95% accuracy. Visual-tactile control policies improve manipulation by 40% over vision-only baselines, achieving 90% success on precise tasks like plug insertion and credit card swiping. All design files, code, trained models, and conversion tools are openly available. Project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

289,055 просмотров • 4 месяцев назад

🧵 Farming robots are no longer experimental. They're deployed, profitable, and reshaping agriculture. In orchards, vineyards, vegetable fields, and beyond, they're tackling labor shortages, precision spraying, and chemical reduction at scale. This is how robotics is quietly becoming the backbone of next-gen agriculture [Save this thread for later 📌]

🧵 Farming robots are no longer experimental. They're deployed, profitable, and reshaping agriculture. In orchards, vineyards, vegetable fields, and beyond, they're tackling labor shortages, precision spraying, and chemical reduction at scale. This is how robotics is quietly becoming the backbone of next-gen agriculture [Save this thread for later 📌]

780,194 просмотров • 1 год назад