Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

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

13,362 subscribers

66,472 görüntüleme • 17 gün önce •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

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 görüntüleme • 9 ay önce

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 görüntüleme • 2 ay önce

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

1,490,155 görüntüleme • 13 gün önce

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 görüntüleme • 5 ay önce

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 görüntüleme • 25 gün önce

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 görüntüleme • 9 ay önce

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

32,025 görüntüleme • 6 ay önce

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

42,072 görüntüleme • 19 gün önce

.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 görüntüleme • 1 ay önce

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 görüntüleme • 1 yıl önce

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

13,325 görüntüleme • 8 ay önce

I left Cameroon in search of my dreams. Resilience, fortitude & courage. These values have helped me to get this far. The road hasn’t been easy. It is clear to me that there is no better place to keep dreaming than in the Theatre of Dreams. Glory, glory Man United.

I left Cameroon in search of my dreams. Resilience, fortitude & courage. These values have helped me to get this far. The road hasn’t been easy. It is clear to me that there is no better place to keep dreaming than in the Theatre of Dreams. Glory, glory Man United.

Andre Onana

5,732,268 görüntüleme • 3 yıl önce

#JanjingjingXTaixiaoxiang 🐯: these days, people keep saying the phrase “to make jan happy,” right? but, today, the winner (i.e., jingjing herself) wants “to make jingjing happy.” 🦊: what should i do? 🐯: well it’s up to p’ to create [soemthing]! 🦊: i don’t know~ you have to instruct me~ i just follow~ i’m a robot~ i just follow~ 🐯: hug until i’m happy/delighted 🦊: 🫂 is this right? 🐯: i’m not that delighted yet 🦊: then what should i do to make you delighted? 🐯: tightly! 🦊: ok tightly~ 🫂

#JanjingjingXTaixiaoxiang 🐯: these days, people keep saying the phrase “to make jan happy,” right? but, today, the winner (i.e., jingjing herself) wants “to make jingjing happy.” 🦊: what should i do? 🐯: well it’s up to p’ to create [soemthing]! 🦊: i don’t know~ you have to instruct me~ i just follow~ i’m a robot~ i just follow~ 🐯: hug until i’m happy/delighted 🦊: 🫂 is this right? 🐯: i’m not that delighted yet 🦊: then what should i do to make you delighted? 🐯: tightly! 🦊: ok tightly~ 🫂

²²

31,831 görüntüleme • 1 ay önce

Smart mapping for robots exploring huge areas! 🗺️ This is called Rolling-Bonxai. When a drone or ground robot maps a massive area, say a whole city or massive warehouse, storing the entire map in memory gets expensive fast. You run out of RAM. This solution is simple, only keep the nearby map in memory. As the robot moves, old chunks save to disk and new chunks load. Like how video games only render what's close to the player. The system divides the map into chunks (imagine a 3D grid of boxes). As the robot explores, it keeps chunks around it loaded in memory. Chunks it's moving away from get saved to disk. When it comes back, they load again. Check the GH repo here 👉🏼 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Smart mapping for robots exploring huge areas! 🗺️ This is called Rolling-Bonxai. When a drone or ground robot maps a massive area, say a whole city or massive warehouse, storing the entire map in memory gets expensive fast. You run out of RAM. This solution is simple, only keep the nearby map in memory. As the robot moves, old chunks save to disk and new chunks load. Like how video games only render what's close to the player. The system divides the map into chunks (imagine a 3D grid of boxes). As the robot explores, it keeps chunks around it loaded in memory. Chunks it's moving away from get saved to disk. When it comes back, they load again. Check the GH repo here 👉🏼 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

15,616 görüntüleme • 1 ay önce

New Golden Gate SOTA: GPT-5.1-Pro! I want to stress that this was _NOT_ one shot - in fact it was many different iterations in 3 different chats. I loved the way it did the water, night sky and the clouds, but it took a lot of back & forth to get the details right - traffic, colours, land. It was quite frustrating that GPT-5.1-Pro wasn't following the instructions after a few steps - it seems like it was struggling to combine the different reasoning threads into a single correct one. But still, this is the best result I got so far.

New Golden Gate SOTA: GPT-5.1-Pro! I want to stress that this was _NOT_ one shot - in fact it was many different iterations in 3 different chats. I loved the way it did the water, night sky and the clouds, but it took a lot of back & forth to get the details right - traffic, colours, land. It was quite frustrating that GPT-5.1-Pro wasn't following the instructions after a few steps - it seems like it was struggling to combine the different reasoning threads into a single correct one. But still, this is the best result I got so far.

Peter Gostev

100,088 görüntüleme • 8 ay önce

The All-In Podcast discussed Figure's AI breakthrough this week I believe this AI breakthrough was essential to enabling a billion robots on the planet - allowing humans to communicate with them and have them carry out actions Helix, our internal AI model, powers the Figure 02 robot. The robot can now generalize to objects it has never seen before and can semantically plan responses to spoken commands, such as "put the groceries away where you think they should go" It’s important to note: the robot’s actuators are not the limiting factor. Right now, both dexterity and actuator speed are constrained by the software. In fact, the actuators are capable of operating at more than 5x their current speed, but our software is holding them back. Over time, as Helix improves, the robot will ultimately surpass human speeds I like these guys. Looking forward to having Chamath Palihapitiya at Figure HQ to see these robots in action!

The All-In Podcast discussed Figure's AI breakthrough this week I believe this AI breakthrough was essential to enabling a billion robots on the planet - allowing humans to communicate with them and have them carry out actions Helix, our internal AI model, powers the Figure 02 robot. The robot can now generalize to objects it has never seen before and can semantically plan responses to spoken commands, such as "put the groceries away where you think they should go" It’s important to note: the robot’s actuators are not the limiting factor. Right now, both dexterity and actuator speed are constrained by the software. In fact, the actuators are capable of operating at more than 5x their current speed, but our software is holding them back. Over time, as Helix improves, the robot will ultimately surpass human speeds I like these guys. Looking forward to having Chamath Palihapitiya at Figure HQ to see these robots in action!

Brett Adcock

135,378 görüntüleme • 1 yıl önce

Decades of hardware development led to strong, fast, and precise robot arms. The moment we can put in general intelligence in these things, we can leverage the full spectra of capabilities that they were always meant to capture. We’re betting on a future where robot hardware will continue to improve, and we intend to build the best models on top of the best hardware to push the frontier of capabilities and reliability. Here’s an old video from TossingBot that I think helps make this point extra clear. Industrial-grade repeatability started out as a crutch for dumb software -- but if you pair it with the right AI models, then it becomes an advantage that is superhuman. There are factories where the same UR robot arms are still being used to precisely and repeatably build the same car parts, operating for 10 yrs straight without a single failure or shutdown. Humanoids will get there too (among other form factors). Not yet today, but eventually. And our models will be ready to meet them when they do.

Decades of hardware development led to strong, fast, and precise robot arms. The moment we can put in general intelligence in these things, we can leverage the full spectra of capabilities that they were always meant to capture. We’re betting on a future where robot hardware will continue to improve, and we intend to build the best models on top of the best hardware to push the frontier of capabilities and reliability. Here’s an old video from TossingBot that I think helps make this point extra clear. Industrial-grade repeatability started out as a crutch for dumb software -- but if you pair it with the right AI models, then it becomes an advantage that is superhuman. There are factories where the same UR robot arms are still being used to precisely and repeatably build the same car parts, operating for 10 yrs straight without a single failure or shutdown. Humanoids will get there too (among other form factors). Not yet today, but eventually. And our models will be ready to meet them when they do.

Andy Zeng

19,174 görüntüleme • 3 ay önce

Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!

Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!

Lukas Ziegler

233,110 görüntüleme • 10 ay önce

Feeling what a robot feels is becoming real! 🫰 Fluid Reality just ran its first full end-to-end touch teleoperation system, and the demo shows why high-resolution haptics might be the missing piece in robot control. A 22 mm fingertip display with 32 independently actuated “bubbles” was mapped directly to tactile sensors on a robot hand. 🫧 Three fingers streamed real-time touch data robot → human, giving the operator actual contact feedback instead of waving their hands blind, like most teleop systems today. It’s still early, but this is a real step toward dexterous ops and high-quality data for training Physical AI systems. Companies involved: Samsung Electronics, Alt-Bionics, Inc. (the robot hand), MANUS™ (hand tracking), and Sensible Robotics (fingertip sensors) Touch isn’t a nice-to-have in robotics. It’s the difference between manipulation that works in the real world P.S. Guess how many touch receptors we humans, have in our hand! :) ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

Feeling what a robot feels is becoming real! 🫰 Fluid Reality just ran its first full end-to-end touch teleoperation system, and the demo shows why high-resolution haptics might be the missing piece in robot control. A 22 mm fingertip display with 32 independently actuated “bubbles” was mapped directly to tactile sensors on a robot hand. 🫧 Three fingers streamed real-time touch data robot → human, giving the operator actual contact feedback instead of waving their hands blind, like most teleop systems today. It’s still early, but this is a real step toward dexterous ops and high-quality data for training Physical AI systems. Companies involved: Samsung Electronics, Alt-Bionics, Inc. (the robot hand), MANUS™ (hand tracking), and Sensible Robotics (fingertip sensors) Touch isn’t a nice-to-have in robotics. It’s the difference between manipulation that works in the real world P.S. Guess how many touch receptors we humans, have in our hand! :) ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

46,927 görüntüleme • 8 ay önce