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BaBot: The Ball-Balancing Robot - Real-time PID control on a 2-axis platform, powered by a microcontroller using the same chip as an Arduino. - Precision servos and IR sensors track the ball with speed and accuracy. - Perfect for learning control systems, teaching robotics, or showing off your engineering... show more

Wevolver

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48,877 views • 1 year ago •via X (Twitter)

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BaBot: A Ball-Balancing Robotics Kit BaBot is a do-it-yourself ball-balancing robot kit designed as a hands-on platform for learning robotics and control systems. It enables users to explore concepts such as PID control, sensors, actuators, and software integration through practical experimentation. The kit is intended for students, makers, and others interested in applied robotics without requiring a formal engineering background. Credit: Babot Project #arduino #ai #robotics #3dprint #engineering

BaBot: A Ball-Balancing Robotics Kit BaBot is a do-it-yourself ball-balancing robot kit designed as a hands-on platform for learning robotics and control systems. It enables users to explore concepts such as PID control, sensors, actuators, and software integration through practical experimentation. The kit is intended for students, makers, and others interested in applied robotics without requiring a formal engineering background. Credit: Babot Project #arduino #ai #robotics #3dprint #engineering

Wevolver

25,314 views • 5 months ago

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 →

Lukas Ziegler

1,190,276 views • 3 months ago

From simulation to reality 🤖 Robotics creator Skyentific built a walking bipedal robot using a simulation-first approach to design, test, and iterating in virtual environments before deploying in the real world. Powered by the NVIDIA Isaac platform and NVIDIA Jetson for on-device AI and control. 📖 #NationalRoboticsWeek

From simulation to reality 🤖 Robotics creator Skyentific built a walking bipedal robot using a simulation-first approach to design, test, and iterating in virtual environments before deploying in the real world. Powered by the NVIDIA Isaac platform and NVIDIA Jetson for on-device AI and control. 📖 #NationalRoboticsWeek

NVIDIA Robotics

21,774 views • 3 months ago

China is scaling humanoid robotics at an insane speed. Super realistic robots from Ex-Robots are now reportedly entering mass production 🤖 - Not prototypes. - Not lab experiments. - Actual production. The biggest shift happening in robotics isn’t just intelligence anymore. It’s making robots look and behave socially acceptable around humans. And honestly… we’re reaching the point where some people may not immediately realize they’re talking to a robot. Exciting future or uncomfortable future? Media : Ex-Robots ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

China is scaling humanoid robotics at an insane speed. Super realistic robots from Ex-Robots are now reportedly entering mass production 🤖 - Not prototypes. - Not lab experiments. - Actual production. The biggest shift happening in robotics isn’t just intelligence anymore. It’s making robots look and behave socially acceptable around humans. And honestly… we’re reaching the point where some people may not immediately realize they’re talking to a robot. Exciting future or uncomfortable future? Media : Ex-Robots ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

CTO ROBOTICS Media

13,284 views • 1 month ago

I believe solving robotics = 90% engineering + 10% research vision. Project GR00T is NVIDIA's moonshot initiative to build physical AGI for humanoid robots. The GEAR Lab is assembling a crack team right now. Join us! Openings: - Sr. Research Engineer, Robotics Systems - Sr. RE, Reinforcement Learning - Sr. RE, Foundation Model Training Infrastructure - Sr. RE, Simulation - Sr. RE, ML Data Pipelines - Research Scientist - Research Intern (both part-time and summer full-time in 2025) For the Sr. positions, we strongly prefer candidates with many years of engineering experience at robotics/autonomous driving companies, or MLOps/large-scale AI teams at big techs. For interns, we welcome ace robotics hackers anywhere! Show me your past works. Job links in the thread. Apply today! Your resumes will be my best Christmas gifts:

I believe solving robotics = 90% engineering + 10% research vision. Project GR00T is NVIDIA's moonshot initiative to build physical AGI for humanoid robots. The GEAR Lab is assembling a crack team right now. Join us! Openings: - Sr. Research Engineer, Robotics Systems - Sr. RE, Reinforcement Learning - Sr. RE, Foundation Model Training Infrastructure - Sr. RE, Simulation - Sr. RE, ML Data Pipelines - Research Scientist - Research Intern (both part-time and summer full-time in 2025) For the Sr. positions, we strongly prefer candidates with many years of engineering experience at robotics/autonomous driving companies, or MLOps/large-scale AI teams at big techs. For interns, we welcome ace robotics hackers anywhere! Show me your past works. Job links in the thread. Apply today! Your resumes will be my best Christmas gifts:

Jim Fan

103,177 views • 1 year ago

At some point when reviewing plays, the league should consider adding a speed threshold for anything involving the element of time. When you slow plays down to 1/100th the speed, it distorts what actually happened and makes it look like, in this case, Cooks possessed the ball for seconds prior to losing it. The game is not played in slow motion or frame by frame. For a catch: A) Secure control of the ball ✅ B) Two feet down in bounds ✅ C) After (a) and (b) have been fulfilled, clearly performs any act common to the game (e.g., extend the ball forward, take an additional step, tuck the ball away and turn upfield, or avoid or ward off an opponent), or he maintains control of the ball long enough to do so. C is where there is a judgement needed since A and B are clearly met. Now consider this note to the rule: If a player, who satisfied (a) and (b), but has not satisfied (c), contacts the ground and loses control of the ball, it is an incomplete pass if the ball hits the ground before he regains control, or if he regains control out of bounds. Because Cooks did lose control of the ball when he contacted the ground and the ball never contacted the ground, it was ruled an interception by Denver.

At some point when reviewing plays, the league should consider adding a speed threshold for anything involving the element of time. When you slow plays down to 1/100th the speed, it distorts what actually happened and makes it look like, in this case, Cooks possessed the ball for seconds prior to losing it. The game is not played in slow motion or frame by frame. For a catch: A) Secure control of the ball ✅ B) Two feet down in bounds ✅ C) After (a) and (b) have been fulfilled, clearly performs any act common to the game (e.g., extend the ball forward, take an additional step, tuck the ball away and turn upfield, or avoid or ward off an opponent), or he maintains control of the ball long enough to do so. C is where there is a judgement needed since A and B are clearly met. Now consider this note to the rule: If a player, who satisfied (a) and (b), but has not satisfied (c), contacts the ground and loses control of the ball, it is an incomplete pass if the ball hits the ground before he regains control, or if he regains control out of bounds. Because Cooks did lose control of the ball when he contacted the ground and the ball never contacted the ground, it was ruled an interception by Denver.

Gene Steratore

4,462,387 views • 6 months ago

Engineers: “This is a breakthrough in soft robotics.” Twitter: “Bro built an AI vibrator.” 🤦‍♂️ Researchers at the University of Southern Denmark created a soft robot that moves by inflating and contracting its body like a worm. Jokes aside… robots like this could actually be useful for rescue missions and environments where traditional robots fail. But let’s be honest: you already know what most comment sections are going to talk about 💀 🎥 Media: SDU Soft Robotics ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

Engineers: “This is a breakthrough in soft robotics.” Twitter: “Bro built an AI vibrator.” 🤦‍♂️ Researchers at the University of Southern Denmark created a soft robot that moves by inflating and contracting its body like a worm. Jokes aside… robots like this could actually be useful for rescue missions and environments where traditional robots fail. But let’s be honest: you already know what most comment sections are going to talk about 💀 🎥 Media: SDU Soft Robotics ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

CTO ROBOTICS Media

416,940 views • 1 month ago

Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.

Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.

Pierre-Alexandre Balland

185,895 views • 6 months ago

Had an amazing time at the Stanford Robotics Center Launch event this Saturday! The Packard building’s underground floor has been transformed into a bright new robotics lab, complete with a mocap room, specialized spaces for domestic, field, and surgical robots, and even an aquarium in progress for the Ocean One bot! Check out the videos below—there’s one of me operating a Da Vinci surgical robot 🤖 Robotics truly embodies interdisciplinary collaboration, pulling together expertise from electrical engineering, mechanical engineering, computer science, materials science, HCI, and design. It’s the kind of field where no single department could drive research forward alone. This new center is an incredible resource to unite researchers, and I have to admit, I’m a bit envious of the PhD students who get to work in such an inspiring environment! Look forward to more great research work from Stanford!

Had an amazing time at the Stanford Robotics Center Launch event this Saturday! The Packard building’s underground floor has been transformed into a bright new robotics lab, complete with a mocap room, specialized spaces for domestic, field, and surgical robots, and even an aquarium in progress for the Ocean One bot! Check out the videos below—there’s one of me operating a Da Vinci surgical robot 🤖 Robotics truly embodies interdisciplinary collaboration, pulling together expertise from electrical engineering, mechanical engineering, computer science, materials science, HCI, and design. It’s the kind of field where no single department could drive research forward alone. This new center is an incredible resource to unite researchers, and I have to admit, I’m a bit envious of the PhD students who get to work in such an inspiring environment! Look forward to more great research work from Stanford!

Charles Qi

17,886 views • 1 year ago

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 →

Lukas Ziegler

54,776 views • 7 months ago

Train a TensorFlow object detection model – then deploy it on a robot 🤖 Iulia Feroli (Iulia Feroli) shows how to turn a notebook into a real-time object detection app. This tutorial works for any project – though we demonstrate the deployment on (and assisted by!) the #ReachyMini, an open-source robot from Pollen Robotics. Built with PyCharm + Claude Code. 👉 Watch it in action:

Train a TensorFlow object detection model – then deploy it on a robot 🤖 Iulia Feroli (Iulia Feroli) shows how to turn a notebook into a real-time object detection app. This tutorial works for any project – though we demonstrate the deployment on (and assisted by!) the #ReachyMini, an open-source robot from Pollen Robotics. Built with PyCharm + Claude Code. 👉 Watch it in action:

PyCharm, a JetBrains IDE

34,908 views • 2 months ago

This Is What A $500,000 Suspension System Looks Like Modern trophy trucks and high-performance off-road racing vehicles use some of the most advanced suspension systems ever built. Designed to absorb massive impacts at high speeds, these systems allow vehicles to remain stable and controllable while traveling across rough terrain, jumps, rocks, and desert landscapes that would destroy conventional suspensions. Built for extreme endurance and performance, components like long-travel shocks, bypass dampers, and custom suspension geometry represent decades of engineering focused on maximizing speed, durability, and control in some of the harshest racing environments on Earth. suspension system, trophy truck, off road racing, automotive engineering, vehicle suspension, racing technology, off road vehicle, shock absorbers, engineering, mechanical engineering, automotive innovation, desert racing, motorsports, suspension technology, performance engineering, high performance vehicles, racing suspension, vehicle dynamics, automotive technology, engineering innovation

This Is What A $500,000 Suspension System Looks Like Modern trophy trucks and high-performance off-road racing vehicles use some of the most advanced suspension systems ever built. Designed to absorb massive impacts at high speeds, these systems allow vehicles to remain stable and controllable while traveling across rough terrain, jumps, rocks, and desert landscapes that would destroy conventional suspensions. Built for extreme endurance and performance, components like long-travel shocks, bypass dampers, and custom suspension geometry represent decades of engineering focused on maximizing speed, durability, and control in some of the harshest racing environments on Earth. suspension system, trophy truck, off road racing, automotive engineering, vehicle suspension, racing technology, off road vehicle, shock absorbers, engineering, mechanical engineering, automotive innovation, desert racing, motorsports, suspension technology, performance engineering, high performance vehicles, racing suspension, vehicle dynamics, automotive technology, engineering innovation

Mechanical Knowledge

25,800 views • 1 month ago

As a newly appointed 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 at Imperial College London, I'm thrilled to announce the 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) at 𝗜𝗺𝗽𝗲𝗿𝗶𝗮𝗹 𝗖𝗼𝗹𝗹𝗲𝗴𝗲 𝗟𝗼𝗻𝗱𝗼𝗻. 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) ( is a new research lab focused on the intersection of safety and intelligence in next-generation robotics. We're hiring exceptional PhD students who are passionate about pushing the boundaries of robot learning. 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗦𝗪𝗜𝗥𝗟 𝘂𝗻𝗶𝗾𝘂𝗲? We operate at the exciting convergence of: • Online & offline reinforcement learning • Imitation learning & human demonstrations • Sample-efficient learning methods • Whole-body and soft robotics systems We're 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲 𝗣𝗵𝗗 𝘀𝘁𝘂𝗱𝗲𝗻𝘁𝘀 interested in: • Developing safe exploration algorithms for robotic systems • Creating sample-efficient learning methods that minimize real-world trials • Building foundation models for robotics with safety guarantees • Advancing soft robotics and compliant human-robot interaction • Bridging theory and practice in embodied AI Why now? As robots become more capable and work closer with humans, we need systems that are both intelligent enough to handle complex tasks 𝗔𝗡𝗗 safe enough for real-world deployment. Traditional approaches treat safety and intelligence as competing priorities, we believe they're synergistic. If you're a motivated researcher who wants to develop the theoretical foundations and practical algorithms for tomorrow's safe, intelligent robots, I'd love to hear from you. Want to join? Apply via

As a newly appointed 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 at Imperial College London, I'm thrilled to announce the 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) at 𝗜𝗺𝗽𝗲𝗿𝗶𝗮𝗹 𝗖𝗼𝗹𝗹𝗲𝗴𝗲 𝗟𝗼𝗻𝗱𝗼𝗻. 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) ( is a new research lab focused on the intersection of safety and intelligence in next-generation robotics. We're hiring exceptional PhD students who are passionate about pushing the boundaries of robot learning. 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗦𝗪𝗜𝗥𝗟 𝘂𝗻𝗶𝗾𝘂𝗲? We operate at the exciting convergence of: • Online & offline reinforcement learning • Imitation learning & human demonstrations • Sample-efficient learning methods • Whole-body and soft robotics systems We're 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲 𝗣𝗵𝗗 𝘀𝘁𝘂𝗱𝗲𝗻𝘁𝘀 interested in: • Developing safe exploration algorithms for robotic systems • Creating sample-efficient learning methods that minimize real-world trials • Building foundation models for robotics with safety guarantees • Advancing soft robotics and compliant human-robot interaction • Bridging theory and practice in embodied AI Why now? As robots become more capable and work closer with humans, we need systems that are both intelligent enough to handle complex tasks 𝗔𝗡𝗗 safe enough for real-world deployment. Traditional approaches treat safety and intelligence as competing priorities, we believe they're synergistic. If you're a motivated researcher who wants to develop the theoretical foundations and practical algorithms for tomorrow's safe, intelligent robots, I'd love to hear from you. Want to join? Apply via

Stephen James

16,552 views • 9 months ago

The robotics industry is about to go through the same shift software did 10 years ago. Here's why the next billion-dollar robotics company will be built by a creator — not a corporation 👇 1/ Corporate robotics requires millions in capital, years of R&D, and a massive team just to ship a product. Creators with the right platform can prototype an idea in weeks, validate with real customers, and iterate fast. 2/ This isn't theory. It's the same pattern we saw with: GitHub → software developers App Store → mobile creators YouTube → video creators Every major platform shift minted a new class of independent builders. Robotics is next. 3/ The barrier isn't talent. There are brilliant engineers everywhere — Ohio, Lagos, Mumbai, Berlin. The barrier is access. Access to tools, infrastructure, and a platform that lets them build and monetize. 4/ That's exactly what $ROBA is building — an open platform where creators build, train, share, and monetize robotic behaviors. No corporate gatekeepers. No vendor lock-in. Just creators owning their innovations. Join the revolution today.

The robotics industry is about to go through the same shift software did 10 years ago. Here's why the next billion-dollar robotics company will be built by a creator — not a corporation 👇 1/ Corporate robotics requires millions in capital, years of R&D, and a massive team just to ship a product. Creators with the right platform can prototype an idea in weeks, validate with real customers, and iterate fast. 2/ This isn't theory. It's the same pattern we saw with: GitHub → software developers App Store → mobile creators YouTube → video creators Every major platform shift minted a new class of independent builders. Robotics is next. 3/ The barrier isn't talent. There are brilliant engineers everywhere — Ohio, Lagos, Mumbai, Berlin. The barrier is access. Access to tools, infrastructure, and a platform that lets them build and monetize. 4/ That's exactly what $ROBA is building — an open platform where creators build, train, share, and monetize robotic behaviors. No corporate gatekeepers. No vendor lock-in. Just creators owning their innovations. Join the revolution today.

Roba Labs

15,225 views • 2 months ago

Mini 6 dof Arm. 3D printed planetary gearboxs & more… [📍GitHub link below ] A mini 6-axis arm driven by stepper motors with custom 3D printed split ring planetary gearboxs and an inverted belt differential wrist with custom bearings, driven by low-cost stepper motors and TMC5150 drivers. Custom firmware was written in C for the STM32 MCU on an BTT Octopus board, to allow for full closed loop PID control using AS5048a encoders daisy-chained over SPI. The controller takes joint targets and returns joint states to a Raspberry Pi 5 streamed over CAN bus. All credit to James Gullberg: 📍GitHub: —— Weekly robotics and AI insights. Subscribe free:

Mini 6 dof Arm. 3D printed planetary gearboxs & more… [📍GitHub link below ] A mini 6-axis arm driven by stepper motors with custom 3D printed split ring planetary gearboxs and an inverted belt differential wrist with custom bearings, driven by low-cost stepper motors and TMC5150 drivers. Custom firmware was written in C for the STM32 MCU on an BTT Octopus board, to allow for full closed loop PID control using AS5048a encoders daisy-chained over SPI. The controller takes joint targets and returns joint states to a Raspberry Pi 5 streamed over CAN bus. All credit to James Gullberg: 📍GitHub: —— Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

33,958 views • 2 months ago

ENGINEAI just opened registration for URKL, a global humanoid fighting league with an insane ¥10,000,000 (approx. $1.39 million) top prize. 🤖🥊 This is a massive engineering challenge focused on motion control and balance using the "T800" humanoid as the standard bot. The rules are strictly "non-violent," meaning no destructive mods are allowed. You win through better code and smarter protective gear. Here is the breakdown for teams looking to jump in: ➤ Massive Payouts: The winner takes ¥10,000,000 (approx. $1.39 million), second gets ¥2,000,000 (approx. $278,000), and third takes ¥1,000,000 (approx. $139,000). ➤ Hardware Perks: Every team that makes it into the Top 16 officially owns their T800 robot. ➤ Career Fast-Track: Top 8 finalists get a "Green Channel" straight to the final interview for job offers at ENGINEAI. ➤ Registration: Open from March 1 to April 30. Teams need at least 3 members with skills in control, electronics, or mechanical design. ➤ Global Finals: After the qualifiers, the world championship is set for December 2026 through January 2027. Once you are in, the committee hands over the simulation platform and T800 models to start training your boxing algorithms. Full Info: #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #URKL #ENGINEAI #RobotFighting

ENGINEAI just opened registration for URKL, a global humanoid fighting league with an insane ¥10,000,000 (approx. $1.39 million) top prize. 🤖🥊 This is a massive engineering challenge focused on motion control and balance using the "T800" humanoid as the standard bot. The rules are strictly "non-violent," meaning no destructive mods are allowed. You win through better code and smarter protective gear. Here is the breakdown for teams looking to jump in: ➤ Massive Payouts: The winner takes ¥10,000,000 (approx. $1.39 million), second gets ¥2,000,000 (approx. $278,000), and third takes ¥1,000,000 (approx. $139,000). ➤ Hardware Perks: Every team that makes it into the Top 16 officially owns their T800 robot. ➤ Career Fast-Track: Top 8 finalists get a "Green Channel" straight to the final interview for job offers at ENGINEAI. ➤ Registration: Open from March 1 to April 30. Teams need at least 3 members with skills in control, electronics, or mechanical design. ➤ Global Finals: After the qualifiers, the world championship is set for December 2026 through January 2027. Once you are in, the committee hands over the simulation platform and T800 models to start training your boxing algorithms. Full Info: #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #URKL #ENGINEAI #RobotFighting

RoboHub🤖

30,637 views • 4 months ago

Meet Seeed at #GTC2026 in Day1! We're live with: ▶️ #reBot B601 Arm: Watch it doing real-time teleoperation + NVIDIA Robotics Isaac Sim visualization. ▶️ #Openclaw+#JetsonThor→Robot Control: Jetson Thor running local #LLMs to control a robot with natural language. ▶️ #ReachyMini: powered by the #reComputer J4012 with #JetsonOrinNX, reading your vibe with on-device vision & AI. Touch, test, and talk tech with us! 📍San Jose, California, USA 📅 March 16th–19th 🏛️ San Jose Convention Centee, Booth 156 #theAIHardwarePartner

Meet Seeed at #GTC2026 in Day1! We're live with: ▶️ #reBot B601 Arm: Watch it doing real-time teleoperation + NVIDIA Robotics Isaac Sim visualization. ▶️ #Openclaw+#JetsonThor→Robot Control: Jetson Thor running local #LLMs to control a robot with natural language. ▶️ #ReachyMini: powered by the #reComputer J4012 with #JetsonOrinNX, reading your vibe with on-device vision & AI. Touch, test, and talk tech with us! 📍San Jose, California, USA 📅 March 16th–19th 🏛️ San Jose Convention Centee, Booth 156 #theAIHardwarePartner

Seeed Studio

13,558 views • 4 months ago

Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.

Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.

Robora

23,489 views • 9 months ago