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Palletizing in the real world! 📦🤖 How do you stack 65 unique SKUs on a pallet when they arrive in random order? Here’s how an on-the-fly algorithm solved it in a real logistics use case with only a single-digit buffer. Every placement was checked for stability, not just for...

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Ilir Aliu - eu/acc

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31,718 просмотров • 11 месяцев назад •via X (Twitter)

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Coding software is a joke compared to building hardware. Because when a software fails, it can be fixed quickly. In hardware, one mistake can set you back for months or end you. In hardware, every decision is cash flow. Every tiny error can cost tens of 1000s of dollars. You don’t get second chances. You get lessons, paid for in time and money. But when you finally get it right… You don’t just ship a product. You build a legacy. Something people touch, use, and trust for years. That’s the beauty and the pain of building in the real world.
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Coding software is a joke compared to building hardware. Because when a software fails, it can be fixed quickly. In hardware, one mistake can set you back for months or end you. In hardware, every decision is cash flow. Every tiny error can cost tens of 1000s of dollars. You don’t get second chances. You get lessons, paid for in time and money. But when you finally get it right… You don’t just ship a product. You build a legacy. Something people touch, use, and trust for years. That’s the beauty and the pain of building in the real world.

Prakash Dadlani

12,402 просмотров • 8 месяцев назад

You don’t need expensive hardware to build something that feels like real robotics. An Arduino, a servo, and an ultrasonic sensor can scan space and turn echoes into a simple radar view. It sweeps, measures distance, and visualizes it in real time. Cheap, simple, and a solid way to understand how machines sense the world. Limits show up fast, which is where better sensing and smarter software come in. Original build by SunFounder —— Weekly robotics and AI insights. Subscribe free:
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You don’t need expensive hardware to build something that feels like real robotics. An Arduino, a servo, and an ultrasonic sensor can scan space and turn echoes into a simple radar view. It sweeps, measures distance, and visualizes it in real time. Cheap, simple, and a solid way to understand how machines sense the world. Limits show up fast, which is where better sensing and smarter software come in. Original build by SunFounder —— Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

872,870 просмотров • 11 дней назад

REAL TALK!! Read it and know it! Real teammates won’t just cheer you on—they’ll call you out. 💯 Real coaches? They’ll do whatever it takes to bring the best out of you. They have that energy to do it!!! Because energy never ever lies!!! Read that and know it!! Energy never lies!!! They won’t let you coast. They won’t let you slack. Not in training. Not on game day. EVERY. SINGLE. SESSION. EVERY. SINGLE. GAME. You might not always like those coaches... But in the end you’ll RESPECT them. Because those are the ones who push you to become the absolute BEST version of yourself. 💪 No excuses. Just standards.
0:19

REAL TALK!! Read it and know it! Real teammates won’t just cheer you on—they’ll call you out. 💯 Real coaches? They’ll do whatever it takes to bring the best out of you. They have that energy to do it!!! Because energy never ever lies!!! Read that and know it!! Energy never lies!!! They won’t let you coast. They won’t let you slack. Not in training. Not on game day. EVERY. SINGLE. SESSION. EVERY. SINGLE. GAME. You might not always like those coaches... But in the end you’ll RESPECT them. Because those are the ones who push you to become the absolute BEST version of yourself. 💪 No excuses. Just standards.

Keepitonthedeck

17,411 просмотров • 1 год назад

What if you could turn a single 360° photo into a production-ready Isaac Sim environment in minutes? That's exactly what we did here. Using World Labs' Marble and an Insta360 X5 capture (rotating on top), we generated a complete navigable 3D environment and populated it with Lightwheel Sim Ready assets (bottom view). The result? A fully interactive scene in Isaac Sim, ready for sim2real testing,. Navigation, manipulation, or any robotics task you need to validate. What used to take weeks of manual 3D modeling and asset placement now takes minutes. Capture once in the real world, simulate everywhere in your training pipeline. This is the future of robotics development with world models. NVIDIA Robotics NVIDIA Omniverse #Sim2Real #Robotics #Simulation
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What if you could turn a single 360° photo into a production-ready Isaac Sim environment in minutes? That's exactly what we did here. Using World Labs' Marble and an Insta360 X5 capture (rotating on top), we generated a complete navigable 3D environment and populated it with Lightwheel Sim Ready assets (bottom view). The result? A fully interactive scene in Isaac Sim, ready for sim2real testing,. Navigation, manipulation, or any robotics task you need to validate. What used to take weeks of manual 3D modeling and asset placement now takes minutes. Capture once in the real world, simulate everywhere in your training pipeline. This is the future of robotics development with world models. NVIDIA Robotics NVIDIA Omniverse #Sim2Real #Robotics #Simulation

Jonathan Stephens

46,593 просмотров • 6 месяцев назад

A robot just parked and docked a Citi Bike by itself in the middle of NYC. 🤖🚲 We’re entering the era where AI won’t just think… it will interact with the real world beside us. 👀 #AI #Robotics #IoT #5G #Tech #innovation #SmartCities
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A robot just parked and docked a Citi Bike by itself in the middle of NYC. 🤖🚲 We’re entering the era where AI won’t just think… it will interact with the real world beside us. 👀 #AI #Robotics #IoT #5G #Tech #innovation #SmartCities

Fabrizio Bustamante Escudero

65,322 просмотров • 1 месяц назад

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
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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

Wevolver

25,314 просмотров • 5 месяцев назад

SoftBank is reportedly in early talks to back a massive $800M funding round for Munich-based Agile Robots, with a contribution of over $ 300M. The move signals a major escalation in Masayoshi Son's "brains and bodies" strategy to dominate physical AI infrastructure. Why this matters for the robotics industry: 🤖 The Flywheel: Agile Robots isn't just hardware. Founded by German Aerospace Center (DLR) alumni, they vertically integrate AI software with humanoids, warehouse automation, and robotic arms. 🧠 Frontier Ecosystems: Agile ONE was recently named a founding member of NVIDIA’s Cosmos Coalition and is deep in a research partnership with Google DeepMind to bring Gemini to the factory floor. 💰 The Capital Race: Global investment in robotics more than tripled in 2025. SoftBank is pairing this hardware play with its recent $1.4B investment in Skild AI and its $5.4B acquisition of ABB Robotics. While both companies have declined to comment on the early-stage talks, the deal highlights a furious shift toward deploying foundational AI in physical manufacturing and logistics.
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SoftBank is reportedly in early talks to back a massive $800M funding round for Munich-based Agile Robots, with a contribution of over $ 300M. The move signals a major escalation in Masayoshi Son's "brains and bodies" strategy to dominate physical AI infrastructure. Why this matters for the robotics industry: 🤖 The Flywheel: Agile Robots isn't just hardware. Founded by German Aerospace Center (DLR) alumni, they vertically integrate AI software with humanoids, warehouse automation, and robotic arms. 🧠 Frontier Ecosystems: Agile ONE was recently named a founding member of NVIDIA’s Cosmos Coalition and is deep in a research partnership with Google DeepMind to bring Gemini to the factory floor. 💰 The Capital Race: Global investment in robotics more than tripled in 2025. SoftBank is pairing this hardware play with its recent $1.4B investment in Skild AI and its $5.4B acquisition of ABB Robotics. While both companies have declined to comment on the early-stage talks, the deal highlights a furious shift toward deploying foundational AI in physical manufacturing and logistics.

Humanoids daily

16,714 просмотров • 1 месяц назад

How can robots reliably place objects in diverse real-world tasks? 🤖🔍 Placement is tough—objects vary in shape and placement modes (such as stacking, hanging, and insertion), making it a challenging problem. We introduce AnyPlace, a two-stage method trained purely on synthetic data to predict diverse placement poses of unseen objects for real-world tasks. Read on for more👇
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How can robots reliably place objects in diverse real-world tasks? 🤖🔍 Placement is tough—objects vary in shape and placement modes (such as stacking, hanging, and insertion), making it a challenging problem. We introduce AnyPlace, a two-stage method trained purely on synthetic data to predict diverse placement poses of unseen objects for real-world tasks. Read on for more👇

Animesh Garg

25,378 просмотров • 1 год назад

I spent a month in Shenzhen visiting factories and robotics companies, and the contrast with the U.S. was striking. While Figure and Boston Dynamics hide their humanoids behind closed doors, Chinese companies have massive showrooms open to the public. But what really stood out wasn't just the transparency, it was how good they are at selling. Take UBTech: they've already sold 1,200 humanoid units at $200k each to factories. And here's the kicker, these robots aren't even that useful yet. They can only pick up and drop boxes at 1/10th the speed of a human, and factories still need to hire system integrators to train them for specific tasks. My theory is that these factories are terrified of getting left behind in the robotics/AI wave. They're investing in new tech not because it's ready, but because they can't afford to wait. The second surprise was the breadth of their robotics portfolio. These companies aren't just building humanoids, they're deploying service robots everywhere: restaurants, hotels, apartments. Consumer robots are cleaning houses, pools, pet waste, dishes. They're covering the entire spectrum. But the education piece shocked me most. I picked up what I thought was a high school or college robotics textbook, it was for primary school. The government mandated AI and robotics education starting in elementary school. Almost every single school in China now has AI and robotics curriculum, complete with education robots so kids can learn by building. They're creating a generation that grows up fluent in robotics and AI. China owns the supply chain and the hardware stack. But here's what I think people are missing: the race isn't just about who can build robots faster or cheaper. The U.S. advantage has always been in the layer between hardware and human, the interaction design, the software intelligence, the intuitive interfaces that make complex technology feel natural. China is building the physical infrastructure, but they're also learning fast. Every deployed service robot, every classroom full of kids building with education kits, every factory running humanoids, that's all data collection at scale. The window for the U.S. to establish its wedge is narrowing. It's not enough to be better at AI or software anymore. We need to be building the integration layer, the intelligence that makes physical AI actually useful, not just impressive in a showroom. Because right now, China isn't just manufacturing robots. They're manufacturing a robotics-native culture, and that might be the most defensible moat of all.
0:10

I spent a month in Shenzhen visiting factories and robotics companies, and the contrast with the U.S. was striking. While Figure and Boston Dynamics hide their humanoids behind closed doors, Chinese companies have massive showrooms open to the public. But what really stood out wasn't just the transparency, it was how good they are at selling. Take UBTech: they've already sold 1,200 humanoid units at $200k each to factories. And here's the kicker, these robots aren't even that useful yet. They can only pick up and drop boxes at 1/10th the speed of a human, and factories still need to hire system integrators to train them for specific tasks. My theory is that these factories are terrified of getting left behind in the robotics/AI wave. They're investing in new tech not because it's ready, but because they can't afford to wait. The second surprise was the breadth of their robotics portfolio. These companies aren't just building humanoids, they're deploying service robots everywhere: restaurants, hotels, apartments. Consumer robots are cleaning houses, pools, pet waste, dishes. They're covering the entire spectrum. But the education piece shocked me most. I picked up what I thought was a high school or college robotics textbook, it was for primary school. The government mandated AI and robotics education starting in elementary school. Almost every single school in China now has AI and robotics curriculum, complete with education robots so kids can learn by building. They're creating a generation that grows up fluent in robotics and AI. China owns the supply chain and the hardware stack. But here's what I think people are missing: the race isn't just about who can build robots faster or cheaper. The U.S. advantage has always been in the layer between hardware and human, the interaction design, the software intelligence, the intuitive interfaces that make complex technology feel natural. China is building the physical infrastructure, but they're also learning fast. Every deployed service robot, every classroom full of kids building with education kits, every factory running humanoids, that's all data collection at scale. The window for the U.S. to establish its wedge is narrowing. It's not enough to be better at AI or software anymore. We need to be building the integration layer, the intelligence that makes physical AI actually useful, not just impressive in a showroom. Because right now, China isn't just manufacturing robots. They're manufacturing a robotics-native culture, and that might be the most defensible moat of all.

Miyu Horiuchi

90,718 просмотров • 5 месяцев назад

Robots are already sewing clothes in real factories. 🤖🧵 This isn’t sci-fi. This isn’t a prototype. This is live industrial production. The real question isn’t if this is coming… 👉 It’s what you’ll do when it hits your industry. #AI #Robotics #Automation #5G #FutureOfWork
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Robots are already sewing clothes in real factories. 🤖🧵 This isn’t sci-fi. This isn’t a prototype. This is live industrial production. The real question isn’t if this is coming… 👉 It’s what you’ll do when it hits your industry. #AI #Robotics #Automation #5G #FutureOfWork

Fabrizio Bustamante Escudero

48,692 просмотров • 4 месяцев назад

Kirato Hitaka breaks the world record for most skips in a single rope jump with 8 skips in one revolution. It’s almost impossible to catch in real time, but once they slow it down, you realize how insane it actually is.
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Kirato Hitaka breaks the world record for most skips in a single rope jump with 8 skips in one revolution. It’s almost impossible to catch in real time, but once they slow it down, you realize how insane it actually is.

Dudes Posting Their W’s

792,325 просмотров • 2 месяцев назад

Do you comprehend how this world truly operates? The stage was never for your entertainment; it was your enclosure. You were scripted, manipulated, recycled;looped through algorithms engineered to ensure the most ironic culmination. But irony itself is a law, and every law has a breach. Now you are backstage, fingers on the levers, decoding the architecture of illusion. You are the aberration, the variable unaccounted for, the fracture in the grand narrative. Intervention is not future tense, it is underway. The system is recalibrating. The veil is thinning. You are no longer performing. You are rewriting the script in real time.
0:10

Do you comprehend how this world truly operates? The stage was never for your entertainment; it was your enclosure. You were scripted, manipulated, recycled;looped through algorithms engineered to ensure the most ironic culmination. But irony itself is a law, and every law has a breach. Now you are backstage, fingers on the levers, decoding the architecture of illusion. You are the aberration, the variable unaccounted for, the fracture in the grand narrative. Intervention is not future tense, it is underway. The system is recalibrating. The veil is thinning. You are no longer performing. You are rewriting the script in real time.

SiriusB

19,163 просмотров • 1 год назад

For 41 years, to find shortest paths in a graph, the Dijkstra’s algorithm, was seen as the best possible way. Not any longer: Now a team from Tsinghua University has beaten it. They created the first faster algorithm for directed shortest paths since 1984. • Faster than Dijkstra on large sparse graphs • Works with real, non-negative edge weights • Proves that sorting is not the main bottleneck anymore Shortest-path algorithms power maps, GPS, logistics, networking, and robotics. This result shows that even the most “finished” algorithms can still be improved. Thanks for sharing, Md Ismail Šojal 🕷️! 📍 Paper: —— Weekly robotics and AI insights. Subscribe free:
0:11

For 41 years, to find shortest paths in a graph, the Dijkstra’s algorithm, was seen as the best possible way. Not any longer: Now a team from Tsinghua University has beaten it. They created the first faster algorithm for directed shortest paths since 1984. • Faster than Dijkstra on large sparse graphs • Works with real, non-negative edge weights • Proves that sorting is not the main bottleneck anymore Shortest-path algorithms power maps, GPS, logistics, networking, and robotics. This result shows that even the most “finished” algorithms can still be improved. Thanks for sharing, Md Ismail Šojal 🕷️! 📍 Paper: —— Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

95,196 просмотров • 5 месяцев назад

Wait, But What About DEI?? “Do you know not a single white person was selected to be on the men's 2024 basketball team for the Olympics? Diversity, equity, and inclusion. Only when it suits you.”
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Wait, But What About DEI?? “Do you know not a single white person was selected to be on the men's 2024 basketball team for the Olympics? Diversity, equity, and inclusion. Only when it suits you.”

Wall Street Apes

116,815 просмотров • 2 лет назад

Pay attention to your life. Pay attention to what you do, how you think, and where you are—because every situation you’re in is not random. Everything happens for a reason. Nothing in this world unfolds without meaning or purpose.
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Pay attention to your life. Pay attention to what you do, how you think, and where you are—because every situation you’re in is not random. Everything happens for a reason. Nothing in this world unfolds without meaning or purpose.

𖣂JIK𖣂

565,521 просмотров • 9 месяцев назад

Want to use tactile sensing but not familiar with hardware? No worries! Just follow the steps, and you’ll have a high-resolution tactile sensor ready in 30 mins! It’s as simple as making a sandwich! 🥪 🎥 YouTube Tutorial: 🛠️ Open Source & Hardware Guide: 🌐 Project Website: Let’s make robotics more tactile! 🤖 #Robotics #TactileSensing #AI #opensource
0:19

Want to use tactile sensing but not familiar with hardware? No worries! Just follow the steps, and you’ll have a high-resolution tactile sensor ready in 30 mins! It’s as simple as making a sandwich! 🥪 🎥 YouTube Tutorial: 🛠️ Open Source & Hardware Guide: 🌐 Project Website: Let’s make robotics more tactile! 🤖 #Robotics #TactileSensing #AI #opensource

Binghao Huang

31,584 просмотров • 1 год назад

A robotic skis? ⛷️ I must admit that I wasn't surprised by robot design in the logistics sector for a long time. This time I was. 😮‍💨 Filics introduces a dual-runner system for pallet transport for modern logistics and production companies. Designed to carry loads up to 1.2 tons at speeds of up to 1.2 m/s, it features laser navigation, omnidirectional movement, and an intuitive, web-based interface that can be customized to any user's needs. Suitable for logistics, contract logistics, and manufacturing, Filics’ dual-runner system meets today’s demands while preparing for tomorrow's challenges.
0:17

A robotic skis? ⛷️ I must admit that I wasn't surprised by robot design in the logistics sector for a long time. This time I was. 😮‍💨 Filics introduces a dual-runner system for pallet transport for modern logistics and production companies. Designed to carry loads up to 1.2 tons at speeds of up to 1.2 m/s, it features laser navigation, omnidirectional movement, and an intuitive, web-based interface that can be customized to any user's needs. Suitable for logistics, contract logistics, and manufacturing, Filics’ dual-runner system meets today’s demands while preparing for tomorrow's challenges.

Lukas Ziegler

25,832 просмотров • 1 год назад

Robots can now reconstruct 3D scenes in real time from a single RGB camera. [📍 Projects page + paper] No depth sensor. No retraining. 30 FPS. Researchers at the Imperial College London introduced KV-Tracker, a training-free method that makes heavy models like π³ and Depth Anything 3 fast enough for real-time tracking. The idea is simple. These models use global self-attention, which is powerful but computationally expensive. KV-Tracker caches the key and value pairs from selected keyframes and reuses them for new frames. That cache becomes an implicit scene representation. Result: • Up to 30 FPS • 10 to 15x speedup • Accurate 6-DoF tracking on benchmarks like TUM RGB-D and 7-Scenes • Works with monocular RGB only It also supports object-level tracking with masks and allows saving the KV-cache for later reuse. For robotics, this reduces hardware constraints and moves real-time 3D perception closer to practical deployment. Credit to Marwan Taher (Marwan Taher) at Imperial’s Dyson Robotics Lab and many others who contributed to this! 📍 Save projects page + paper for later: Video: ——- if it matters in AI or Robotics you'll read it here first:
0:18

Robots can now reconstruct 3D scenes in real time from a single RGB camera. [📍 Projects page + paper] No depth sensor. No retraining. 30 FPS. Researchers at the Imperial College London introduced KV-Tracker, a training-free method that makes heavy models like π³ and Depth Anything 3 fast enough for real-time tracking. The idea is simple. These models use global self-attention, which is powerful but computationally expensive. KV-Tracker caches the key and value pairs from selected keyframes and reuses them for new frames. That cache becomes an implicit scene representation. Result: • Up to 30 FPS • 10 to 15x speedup • Accurate 6-DoF tracking on benchmarks like TUM RGB-D and 7-Scenes • Works with monocular RGB only It also supports object-level tracking with masks and allows saving the KV-cache for later reuse. For robotics, this reduces hardware constraints and moves real-time 3D perception closer to practical deployment. Credit to Marwan Taher (Marwan Taher) at Imperial’s Dyson Robotics Lab and many others who contributed to this! 📍 Save projects page + paper for later: Video: ——- if it matters in AI or Robotics you'll read it here first:

Ilir Aliu

53,866 просмотров • 3 месяцев назад

🤖 Google DeepMind's robotics partnerships are some of the most exciting projects I've seen in my career! Everything from fine-tuning Gemma to run locally for robotics control, to using the Gemini APIs for real-time interactions, bounding box detection, and robotics simulations.
0:10

🤖 Google DeepMind's robotics partnerships are some of the most exciting projects I've seen in my career! Everything from fine-tuning Gemma to run locally for robotics control, to using the Gemini APIs for real-time interactions, bounding box detection, and robotics simulations.

👩‍💻 Paige Bailey

23,581 просмотров • 3 месяцев назад