Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

This FlexPCB took many iterations to get right.. But designing these tiny flexures simplified assembly, reduced wiring & helped keep the entire robot compact! Full Project: Robot Kit:

Carl Bugeja

13,564 subscribers

67,061 views • 2 months ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

15 Comments

Hateful YN2 months ago

you can flex your PCB but you can't flex your solder

Pete Art2 months ago

Well done!

Caleb (OSH Cut)2 months ago

Neat!

Robin Debreuil2 months ago

The path to MEMS :). Love how far you are pushing FlexPCBs!

Will Viana2 months ago

gorgeous work and great video

Will Faust2 months ago

So cool!

Wij 🇳🇿2 months ago

This is awesome Carl

tieuho2k72 months ago

awesome!

David Walmroth2 months ago

@sahajsarup

Arrow2 months ago

Really cool!

Santosh Bhargav2 months ago

Brilliant. Have a look at compliant mechanisms. Amazing things can be achieved by engineering flexibility into the design.

SUBØ2 months ago

👏

Gustl Unterhammer 🇩🇪 🇺🇦 🇦🇷🐧🚜2 months ago

Very good work👍

various_12 months ago

If only you'd ship without a battery, it would make more sense at this price point.

Rivers2 months ago

这个柔性套件看起来真的是太棒了。

Related Videos

Well, it's Saturday. A perfect moment to watch a robot giving you a new haircut, right? 💇🏼‍♂️ This robot created by Shane Wighton will not only do a great haircut or trim the sides but is also able to chat with you. During the pandemic, the creator of StuffMadeHere built this robot to give himself a haircut. It offers different types of hairstyles and uses scissors. Parts of the robot were printed using a 3D printer. Fantastic design, but further down the line I'm wondering if I'm brave enough to let the robot give me a trim. Probably not yet. I would like to know more details about the safety and reliability of the system. P.S. What are your honest thoughts on this project?

Well, it's Saturday. A perfect moment to watch a robot giving you a new haircut, right? 💇🏼‍♂️ This robot created by Shane Wighton will not only do a great haircut or trim the sides but is also able to chat with you. During the pandemic, the creator of StuffMadeHere built this robot to give himself a haircut. It offers different types of hairstyles and uses scissors. Parts of the robot were printed using a 3D printer. Fantastic design, but further down the line I'm wondering if I'm brave enough to let the robot give me a trim. Probably not yet. I would like to know more details about the safety and reliability of the system. P.S. What are your honest thoughts on this project?

Lukas Ziegler

58,011 views • 10 months ago

Six arms instead of two! 🤯 Midea Group humanoid robot has six arms instead of two. It handles heavy components with lower limbs and performs fine assembly work with upper limbs. Full 360-degree rotation, stable vertical lifting, rapid tool-swapping. The robot handles workstation transitions that would typically require multiple human workers or separate machines. So no idle-time between stations. Pretty cool. But I'm really curious about the cost, and how this 6-arms robot compares to a regular robot arm, and then to a regular humanoid What do yo think? Overcomplicated? ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Six arms instead of two! 🤯 Midea Group humanoid robot has six arms instead of two. It handles heavy components with lower limbs and performs fine assembly work with upper limbs. Full 360-degree rotation, stable vertical lifting, rapid tool-swapping. The robot handles workstation transitions that would typically require multiple human workers or separate machines. So no idle-time between stations. Pretty cool. But I'm really curious about the cost, and how this 6-arms robot compares to a regular robot arm, and then to a regular humanoid What do yo think? Overcomplicated? ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

12,841 views • 4 months ago

Microduck won't be ready until the end of the year, but why wait? We are thrilled to launch XGO-Duck, a fully open-source robot project you can build right now!100% open. Grab your parts and start DIYing this weekend! 🛠️📷 #Microduck #Robotics #Maker #DIY

Microduck won't be ready until the end of the year, but why wait? We are thrilled to launch XGO-Duck, a fully open-source robot project you can build right now!100% open. Grab your parts and start DIYing this weekend! 🛠️📷 #Microduck #Robotics #Maker #DIY

XGO Robot

51,688 views • 8 days ago

Catching skin cancer early is a home robotics problem. Melanoma is highly treatable when detected early, yet today’s screening process depends heavily on patients noticing tiny changes across their entire skin surface. This requires patients to solve a near-impossible visual-memory and registration problem. I built OpenDerm, an open-source 4-DOF robot that captures high-resolution images of the skin and uses them to reconstruct and track the skin surface in 3D over time. The best way to make skin screening truly routine is to bring it into the home. OpenDerm shows that inexpensive robotic skin imaging is possible, but the path to scale is not a dedicated screening robot in every household—it is to make skin screening one of the many useful things a general-purpose home robot can do. Read more about why I built OpenDerm and how it works here: Blog: Project:

Catching skin cancer early is a home robotics problem. Melanoma is highly treatable when detected early, yet today’s screening process depends heavily on patients noticing tiny changes across their entire skin surface. This requires patients to solve a near-impossible visual-memory and registration problem. I built OpenDerm, an open-source 4-DOF robot that captures high-resolution images of the skin and uses them to reconstruct and track the skin surface in 3D over time. The best way to make skin screening truly routine is to bring it into the home. OpenDerm shows that inexpensive robotic skin imaging is possible, but the path to scale is not a dedicated screening robot in every household—it is to make skin screening one of the many useful things a general-purpose home robot can do. Read more about why I built OpenDerm and how it works here: Blog: Project:

Marion Lepert

1,505,666 views • 2 months ago

There’s MANY possible factors into pelvic deviations & deep hip issues… But these common sensitive & weak points are great opportunities to look at when starting to rebuild this area. Keep curious, keep looking for clues. Play the long game! ❤️‍🩹

There’s MANY possible factors into pelvic deviations & deep hip issues… But these common sensitive & weak points are great opportunities to look at when starting to rebuild this area. Keep curious, keep looking for clues. Play the long game! ❤️‍🩹

Brendan Backstrom

13,174 views • 7 months ago

These guys trained a robot with water bottles, and the robot learned to pick up other objects it had never practiced on. They did this using reinforcement learning: 1. The robot had to pick a bottle out of a messy tote 2. Then it had to hand the bottle to a person 3. Only water bottles. Nothing else. After they finished training, they tested the robot on different objects: • On bottles, the success went from 80% to 98% • On snack cans, the robot's throughput rose 40% • On soft bags, the robot's performance improved by 13% even though they're deformable and much harder to handle than rigid objects. Snack cans and soft bags have different shapes and weights, and the robot was never trained on them. This was just one of three use cases they tested. Every hour we spend teaching a robot costs a ton of money. If they only get better at handling the one object they practice on, reinforcement learning will never be worth doing. But if the gains carry over, we could focus on teaching the hardest possible tasks and let the robot apply that knowledge elsewhere. Here is the full write-up by Humanoid on the infrastructure they used and what they learned: #ad

These guys trained a robot with water bottles, and the robot learned to pick up other objects it had never practiced on. They did this using reinforcement learning: 1. The robot had to pick a bottle out of a messy tote 2. Then it had to hand the bottle to a person 3. Only water bottles. Nothing else. After they finished training, they tested the robot on different objects: • On bottles, the success went from 80% to 98% • On snack cans, the robot's throughput rose 40% • On soft bags, the robot's performance improved by 13% even though they're deformable and much harder to handle than rigid objects. Snack cans and soft bags have different shapes and weights, and the robot was never trained on them. This was just one of three use cases they tested. Every hour we spend teaching a robot costs a ton of money. If they only get better at handling the one object they practice on, reinforcement learning will never be worth doing. But if the gains carry over, we could focus on teaching the hardest possible tasks and let the robot apply that knowledge elsewhere. Here is the full write-up by Humanoid on the infrastructure they used and what they learned: #ad

Santiago

13,952 views • 2 months ago

15–30 minutes of real-world robot data. That's now enough to go from sim-to-real failure to working robot. Let’s see… You train a robot in simulation. You deploy it in the real world. It fails. The physics don't match. So you try to fine-tune it with real data, but… you never have enough real data, and the fine-tuning breaks everything the simulation taught it. SimDist fixes this with one key decision: don't transfer the policy. Transfer the world model. Keep the reward and value knowledge from simulation frozen. Only update the part that's actually wrong, how the robot predicts physics. Now the robot doesn't have to relearn the entire task in the real world. It already knows what success looks like. It just needs to correct its understanding of how the real world moves. The part that makes this work: they also trained on failures and recoveries; not just perfect demonstrations. Without that, the planner finds the gaps and exploits them. With it, the robot can tell a good future from a bad one. That's all it needs. Results on peg insertion, table leg assembly, locomotion on slippery and uneven surfaces. Tasks that require precision, force, and quick reaction. Thanks for sharing, Tyler Westenbroek ([Tyler Westenbroek]. Interactive visualization + paper: ——- Weekly robotics and AI insights. Subscribe free:

15–30 minutes of real-world robot data. That's now enough to go from sim-to-real failure to working robot. Let’s see… You train a robot in simulation. You deploy it in the real world. It fails. The physics don't match. So you try to fine-tune it with real data, but… you never have enough real data, and the fine-tuning breaks everything the simulation taught it. SimDist fixes this with one key decision: don't transfer the policy. Transfer the world model. Keep the reward and value knowledge from simulation frozen. Only update the part that's actually wrong, how the robot predicts physics. Now the robot doesn't have to relearn the entire task in the real world. It already knows what success looks like. It just needs to correct its understanding of how the real world moves. The part that makes this work: they also trained on failures and recoveries; not just perfect demonstrations. Without that, the planner finds the gaps and exploits them. With it, the robot can tell a good future from a bad one. That's all it needs. Results on peg insertion, table leg assembly, locomotion on slippery and uneven surfaces. Tasks that require precision, force, and quick reaction. Thanks for sharing, Tyler Westenbroek ([Tyler Westenbroek]. Interactive visualization + paper: ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

14,222 views • 4 months ago

I asked the server at this sushi place if the robot servers stole her shifts and her answer surprised me. a few years ago they brought in robot servers. The boss started with 1 robot, cut the staff from 5 to 4. From day 1 the robots were a mess. They can basically only deliver drinks. They get in the way. The 4 remaining servers felt about 20% busier, like the robot made no difference. But the kids LOVED them. Adults posted videos to social media like I'm doing right now. This grew their business in an unexpected way. Today they only have 2 robots. Zero shifts replaced (she says). But the robots still deliver drinks and the restaurant is busier than ever. Conveyor belt sushi is brilliant. Familiar to Japan for decades, newer to the US. The more plates you grab, the more prizes you win. Gamification in real life. What this restaurant did is genius. Talk about a flywheel: - Conveyor belt drives social media virality, increasing sales - Robot servers drive social media virality, increasing sales - Gamification drives average order values (The food is pretty garbage BTW, but my kids love the concept and it's a tradition for us) The server was hesitant to admit this, but after working out the robot kinks it sounded like there would be more human shifts today if not for the 2 robots. How many people order drinks JUST to see the robot? They didn't replace humans on a 1:1 ratio. But 1:3 or 1:4, yes. AI and automation will add much more in efficiency and productivity than the jobs it takes. A huge net win.

I asked the server at this sushi place if the robot servers stole her shifts and her answer surprised me. a few years ago they brought in robot servers. The boss started with 1 robot, cut the staff from 5 to 4. From day 1 the robots were a mess. They can basically only deliver drinks. They get in the way. The 4 remaining servers felt about 20% busier, like the robot made no difference. But the kids LOVED them. Adults posted videos to social media like I'm doing right now. This grew their business in an unexpected way. Today they only have 2 robots. Zero shifts replaced (she says). But the robots still deliver drinks and the restaurant is busier than ever. Conveyor belt sushi is brilliant. Familiar to Japan for decades, newer to the US. The more plates you grab, the more prizes you win. Gamification in real life. What this restaurant did is genius. Talk about a flywheel: - Conveyor belt drives social media virality, increasing sales - Robot servers drive social media virality, increasing sales - Gamification drives average order values (The food is pretty garbage BTW, but my kids love the concept and it's a tradition for us) The server was hesitant to admit this, but after working out the robot kinks it sounded like there would be more human shifts today if not for the 2 robots. How many people order drinks JUST to see the robot? They didn't replace humans on a 1:1 ratio. But 1:3 or 1:4, yes. AI and automation will add much more in efficiency and productivity than the jobs it takes. A huge net win.

Chris Koerner

69,583 views • 1 month ago

This is a portion of the force info we get from the hand, both when it's actively controlled and passively wiggled. We damaged some motors (black hexagons) from shipping the robot. But the fingers still have their full range of motion, thanks to the robustness of complexity.

This is a portion of the force info we get from the hand, both when it's actively controlled and passively wiggled. We damaged some motors (black hexagons) from shipping the robot. But the fingers still have their full range of motion, thanks to the robustness of complexity.

Tom Zhang

48,030 views • 11 months ago

A video from a Pi robot deployed at Dandelion Chocolate, fully autonomous w/ no interventions. 🤖 Deploying robots has taught us surprising lessons about the gap between proof-of-concept (i.e. building one box) and real-world utility (productively building boxes for hours). I expected that the hard part is building the box, since it’s the most dexterous, but that wasn't what we found. Counterintuitively, the hardest part was reliably stacking the boxes. Our original table-mounted robot had poor visibility of the stack without special separately-mounted cameras. Plus, stacking requires more generalization (each box is placed in a different location), and an imprecisely-placed box can lead the entire stack to collapse many boxes later. We recently switched this deployment over to a mobile robot, and it's fun to watch the robot being completely self sufficient for multiple hours. 🙂 Data and feedback from real world use-cases like these are quite valuable for the π pre-trained model as we scale!

A video from a Pi robot deployed at Dandelion Chocolate, fully autonomous w/ no interventions. 🤖 Deploying robots has taught us surprising lessons about the gap between proof-of-concept (i.e. building one box) and real-world utility (productively building boxes for hours). I expected that the hard part is building the box, since it’s the most dexterous, but that wasn't what we found. Counterintuitively, the hardest part was reliably stacking the boxes. Our original table-mounted robot had poor visibility of the stack without special separately-mounted cameras. Plus, stacking requires more generalization (each box is placed in a different location), and an imprecisely-placed box can lead the entire stack to collapse many boxes later. We recently switched this deployment over to a mobile robot, and it's fun to watch the robot being completely self sufficient for multiple hours. 🙂 Data and feedback from real world use-cases like these are quite valuable for the π pre-trained model as we scale!

Chelsea Finn

104,016 views • 18 days ago

Open-source robot arm meets hand tracking [📍GitHub below] It is designed with an industrial mindset but built as a 3D-printed desktop system. PAROL6 paired with a LEAP Motion controller is a nice example of how accessible robot teleoperation has become. • Hand motion is streamed to the robot at 100 Hz via UDP • A pneumatic gripper is controlled by simple fist open and close gestures • The entire robot stack is open source, from mechanics to control software Combine that with low-latency hand tracking and you get a very practical platform for learning manipulation, teleoperation, and human-robot interfaces. This kind of setup is great for experimentation, teleop, data collection, and teaching robots by demonstration All without proprietary hardware or locked software. Credit to SourceRobotics 📍Code: —— Weekly robotics and AI insights. Subscribe free:

Open-source robot arm meets hand tracking [📍GitHub below] It is designed with an industrial mindset but built as a 3D-printed desktop system. PAROL6 paired with a LEAP Motion controller is a nice example of how accessible robot teleoperation has become. • Hand motion is streamed to the robot at 100 Hz via UDP • A pneumatic gripper is controlled by simple fist open and close gestures • The entire robot stack is open source, from mechanics to control software Combine that with low-latency hand tracking and you get a very practical platform for learning manipulation, teleoperation, and human-robot interfaces. This kind of setup is great for experimentation, teleop, data collection, and teaching robots by demonstration All without proprietary hardware or locked software. Credit to SourceRobotics 📍Code: —— Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

32,823 views • 12 days ago

Look I’ll admit I haven’t played SOTM or know that much about the more recent lore But saying we can’t relate to The Mimic because it’s a Robot is kinda stupid. I’ve seen SO MANY PEOPLE passionate about its story & character that this statement doesn’t feel remotely true dude

Look I’ll admit I haven’t played SOTM or know that much about the more recent lore But saying we can’t relate to The Mimic because it’s a Robot is kinda stupid. I’ve seen SO MANY PEOPLE passionate about its story & character that this statement doesn’t feel remotely true dude

JackoBee🐝

482,869 views • 1 month ago

everyone is using GPT-6 Astra to make games... i had it build me a robot prototyper i type what robot i want, and it builds the whole thing and tells me how to make it real one prompt: "prototype me a full Microduck" it designed every part, checked nothing crashes into itself when it moves, did the motor maths so the thing can actually stand up, and handed me the parts list with prices and the step by step assembly not a render, a robot i can build this weekend every piece is ready to send straight to a 3D printer, and the motors and screws come with prices and where to buy them took me 45 minutes and 5 prompts to build (burnt all my limits) process below

everyone is using GPT-6 Astra to make games... i had it build me a robot prototyper i type what robot i want, and it builds the whole thing and tells me how to make it real one prompt: "prototype me a full Microduck" it designed every part, checked nothing crashes into itself when it moves, did the motor maths so the thing can actually stand up, and handed me the parts list with prices and the step by step assembly not a render, a robot i can build this weekend every piece is ready to send straight to a 3D printer, and the motors and screws come with prices and where to buy them took me 45 minutes and 5 prompts to build (burnt all my limits) process below

Ronin

59,063 views • 26 days ago

Elon Musk: “Optimus Will Be The Biggest Product Ever Created” Let's see Optimus. You know, as you've heard me say before, I think Optimus will be the biggest product ever. But it is a very complex problem to solve. It's one of the hardest things to solve. To make a humanoid robot that can do tasks that you simply ask it to do, or show it a video, and it can do the task without any programming — like, no one's ever achieved this. And there are many challenges in the electromechanical design of the robot, to achieve sufficient dexterity and reliable hands, to be very reliable and have long, long wear and tear. But, I mean, it's good to be out in the field and not break down. Otherwise, you get this 70-kilogram robot that just flopped over, and you could carry it around like a baby, you know. And we don't want Optimus to go haywire. So, it's a lot of work to scale, to get the design right, and to scale production. And I really want to emphasize here that the production scaling challenge is very, very substantial. So this is going to be the hardest product to scale manufacturing that we've ever made at Tesla, because everything on the robot is new. And the difficulty of scaling the production up is proportionate to the newness of the parts in the robot.

Elon Musk: “Optimus Will Be The Biggest Product Ever Created” Let's see Optimus. You know, as you've heard me say before, I think Optimus will be the biggest product ever. But it is a very complex problem to solve. It's one of the hardest things to solve. To make a humanoid robot that can do tasks that you simply ask it to do, or show it a video, and it can do the task without any programming — like, no one's ever achieved this. And there are many challenges in the electromechanical design of the robot, to achieve sufficient dexterity and reliable hands, to be very reliable and have long, long wear and tear. But, I mean, it's good to be out in the field and not break down. Otherwise, you get this 70-kilogram robot that just flopped over, and you could carry it around like a baby, you know. And we don't want Optimus to go haywire. So, it's a lot of work to scale, to get the design right, and to scale production. And I really want to emphasize here that the production scaling challenge is very, very substantial. So this is going to be the hardest product to scale manufacturing that we've ever made at Tesla, because everything on the robot is new. And the difficulty of scaling the production up is proportionate to the newness of the parts in the robot.

Tesla Owners Silicon Valley

42,131 views • 2 months ago

Today makes 1 year alcohol free wow! To celebrate stream this “so what” that exudes the confidence I thought I’d only have with the liq..play it in the gym, a place that helped keep my mind off that liq…Not on the project but we’ll get there 😈

Today makes 1 year alcohol free wow! To celebrate stream this “so what” that exudes the confidence I thought I’d only have with the liq..play it in the gym, a place that helped keep my mind off that liq…Not on the project but we’ll get there 😈

Cozz

43,115 views • 1 year ago

.pabs broke down the $PEAK origin story and how he stumbled across Virtuals Protocol, the team that helped make this possible Every robotics company refused to give Pablo a robot when he was starting Pemba, worried he'd put it somewhere it would fail and make them look bad Then a friend connected him to Virtuals' Eastworlds Initiative, where he landed a deal in a 30-minute meeting: Here's a free humanoid robot IF you tokenize it Pablo didn't know anything about crypto going in, but now $PEAK is bootstrapping every major expense keeping the project moving forward

.pabs broke down the $PEAK origin story and how he stumbled across Virtuals Protocol, the team that helped make this possible Every robotics company refused to give Pablo a robot when he was starting Pemba, worried he'd put it somewhere it would fail and make them look bad Then a friend connected him to Virtuals' Eastworlds Initiative, where he landed a deal in a 30-minute meeting: Here's a free humanoid robot IF you tokenize it Pablo didn't know anything about crypto going in, but now $PEAK is bootstrapping every major expense keeping the project moving forward

MCG

15,284 views • 3 months ago

Jason Ma reveals the first true scaling law in robotics: robots trained on 1 million hours of first-person human video predictably get better without ever seeing robot data "Yesterday we announced our new flagship robot foundation model called Dyna-2. It's very significant for the entire field for many different reasons. First of all, it's the first robot foundation model trained on at least one million hours of data. That in itself is a very challenging infrastructure challenge." "What we demonstrated is that even if the one million hours of data is entirely first-person video of humans doing manipulation tasks, we actually see scaling law for transferring to robot embodiments that the model has never seen before." "By training on more human data, we actually see predictable performance improvement on robots. That's a big deal because the biggest challenge facing robot foundation models is that we don't have enough data." "Unlike language models, there are just not enough robotics data out there, and it's very difficult to collect these robot data. Only by passively observing humans doing things can we scale this kind of data, and this is the first time we showed there is a lot of improvement that can transfer." Jason Ma Dyna Robotics

Jason Ma reveals the first true scaling law in robotics: robots trained on 1 million hours of first-person human video predictably get better without ever seeing robot data "Yesterday we announced our new flagship robot foundation model called Dyna-2. It's very significant for the entire field for many different reasons. First of all, it's the first robot foundation model trained on at least one million hours of data. That in itself is a very challenging infrastructure challenge." "What we demonstrated is that even if the one million hours of data is entirely first-person video of humans doing manipulation tasks, we actually see scaling law for transferring to robot embodiments that the model has never seen before." "By training on more human data, we actually see predictable performance improvement on robots. That's a big deal because the biggest challenge facing robot foundation models is that we don't have enough data." "Unlike language models, there are just not enough robotics data out there, and it's very difficult to collect these robot data. Only by passively observing humans doing things can we scale this kind of data, and this is the first time we showed there is a lot of improvement that can transfer." Jason Ma Dyna Robotics

MTS

17,740 views • 1 month ago

Los Angeles is full of hardware startups these days - most of them doing defense, energy, manufacturing and aerospace. But this week we bring you the story of a company making a fish killing robot. It's from Shinkei, and it's designed to kill fish in a more humane way using a method perfected in Japan and now automated with a robot. The fish are killed quickly instead of suffocating on a boat. And the result result for humans is better tasting, healthier fish. We went to El Segundo to see how the robot is made and operates and then hopped on a boat to see it in action on the sea. Full episode here made possible by the finance geniuses at Brex.

Los Angeles is full of hardware startups these days - most of them doing defense, energy, manufacturing and aerospace. But this week we bring you the story of a company making a fish killing robot. It's from Shinkei, and it's designed to kill fish in a more humane way using a method perfected in Japan and now automated with a robot. The fish are killed quickly instead of suffocating on a boat. And the result result for humans is better tasting, healthier fish. We went to El Segundo to see how the robot is made and operates and then hopped on a boat to see it in action on the sea. Full episode here made possible by the finance geniuses at Brex.

Ashlee Vance

29,926 views • 27 days ago

When you need us, A&E might seem like the obvious choice – but there are many ways to get help for non-emergencies. For urgent medical help, access NHS 111 by calling, going online or using the NHS App. Get the right care, in the right place, at the right time this winter.

When you need us, A&E might seem like the obvious choice – but there are many ways to get help for non-emergencies. For urgent medical help, access NHS 111 by calling, going online or using the NHS App. Get the right care, in the right place, at the right time this winter.

NHS

13,338 views • 9 months ago