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When robots take the night shift shopping spree! 🛍️ Robots navigate through dm-drogerie markt Deutschland stores at night to create a digital replica of the store's layout, known as a "digital twin." Developed Ubica Robotics GmbH, these autonomous robots scan shelves to provide real-time information about item positions, pricing,... show more

Lukas Ziegler

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64,840 Aufrufe • vor 3 Monaten •via X (Twitter)

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

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

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Robotics is a data problem. Today, we’re partnering with ABB Robotics, Universal Robots, and NVIDIA Robotics to deploy the Skild Brain across real-world industries from manufacturing to factory lines. This will help us build the world’s biggest data flywheel for physical AI.

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The trend in China is that more robotics companies are opening stores where anyone can see and interact with the robots. It’s no longer necessary for everyone to contact a salesperson or visit the company’s office. BTW, I like the store designs of both EngineAI and AgiBot!

The trend in China is that more robotics companies are opening stores where anyone can see and interact with the robots. It’s no longer necessary for everyone to contact a salesperson or visit the company’s office. BTW, I like the store designs of both EngineAI and AgiBot!

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Digital twins make deployments! 🔄 Digital twins are more than just simulation, they let you test and fix everything before touching real hardware. The biggest win is catching problems early. You can test the complete system virtually, including all the control logic and data flows. Finding a bug in simulation takes hours. Finding it on-site during installation takes days and costs serious money. The second benefit is predictable deployment. Instead of discovering surprises when the robots arrive, you've already worked through the issues in the virtual model. The third advantage is automation. The operator interface gets generated automatically from the digital model. The old way was: build the system, write all the code, install the hardware, then spend weeks debugging on-site. Cool example here! ;-) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Digital twins make deployments! 🔄 Digital twins are more than just simulation, they let you test and fix everything before touching real hardware. The biggest win is catching problems early. You can test the complete system virtually, including all the control logic and data flows. Finding a bug in simulation takes hours. Finding it on-site during installation takes days and costs serious money. The second benefit is predictable deployment. Instead of discovering surprises when the robots arrive, you've already worked through the issues in the virtual model. The third advantage is automation. The operator interface gets generated automatically from the digital model. The old way was: build the system, write all the code, install the hardware, then spend weeks debugging on-site. Cool example here! ;-) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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It's the little things that make me excited about the future. Many people are (rightfully) worried that AI and robotics will take their jobs. Yes, it's about money they need to live on, and solutions are needed. At the same time, it's often work that's strenuous and tedious. So we can be glad when robots take these tasks off our hands. Furthermore, robots don't need breaks, vacations, or sleep. They can be scaled quickly and are efficient. Globalization, and humanity as a whole, can therefore benefit massively from this increase in efficiency.

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You don’t need to run a store to earn from it Robots can scan groceries, restock shelves, and share profits with you and other co-owners The future of retail is autonomous, tokenized, and powered by people – on peaq

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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.

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

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Robotics is obsessed with foundation models and humanoids. It’s missing the most critical piece. One founder just raised $3M to build the “AWS for robots.” Fixing the silent bottleneck for most robotics startup: Data Infrastructure: 🧵

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How could robotics soon help us in our daily lives? 🤖 Today, we’re announcing a suite of research advances that enable robots to make decisions faster as well as better understand and navigate their environments. Here's a snapshot of the work. 🧵

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🧵In the world of physical AI, we’re used to seeing videos sped up to hide how slow robots actually are. Eka Robotics, Inc. is doing the exact opposite. They’re showing their robots at 1/25x speed because the movement is so fast and the force-sensitivity so precise, you’d miss the "superhuman" dexterity in real-time.

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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 skills. - Fully open-source & ready to build at Video Credit: Johan Link #engineering #technology #robots #robotics

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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.

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