One professor at the University of Bonn quietly put his entire robotics curriculum on YouTube: SLAM. Sensor fusion. State estimation. Probabilistic robotics. Self-driving cars. Motion planning. Photogrammetry. Cyrill Stachniss has been uploading full university lectures for years! Each topic is a complete playlist; the kind of material that normally costs a semester of tuition. He's one of the most cited researchers in mobile robotics and mapping. His students go on to build the navigation stacks powering real autonomous systems. If you're serious about understanding how robots know where they are... this is the place to start. Free. On YouTube. 📌 [youtube.com/@CyrillStachniss] —— Weekly robotics and AI insights. Subscribe free: 22astronauts.com

C framework for 3D reconstruction from images github.com/openMVG/openMVG

First FreeCAD book copy received! Recently, I have published the FreeCAD Beginner's Handbook and have now received my first own copy. This moment is the result of a lot of ups and downs and is one of the biggest projects of my entire life. I hope you like it. #MadeWithFreeCAD

This sounds way too advanced for our time 😮

Swiss researchers have introduced a technology that sounds like science fiction: a crystal-based battery capable of generating power for centuries without needing to recharge. Built using stable crystalline structures and radioactive decay energy capture, the battery releases a slow, consistent electrical output for hundreds of years. Unlike traditional batteries, it doesn’t degrade, leak, overheat, or lose capacity. Early prototypes show enormous potential for spacecraft, medical implants, AI sensors, underwater systems, and deep-earth machines — devices where replacing a battery is nearly impossible. If scaled, this invention could redefine global energy infrastructure, powering the future with a device that outlives generations.

Why does NVIDIA keeps breaking my daily operations?

ros2_calib Make your calibration dreams come true. ros2_calib is a Multi-Sensor Calibration Tool using ROS2 mcap recordings with direct URDF export. github.com/ika-rwth-aachen/r…

This morning, I presented our paper with about REALMS2 for the ESA-ESRIC Space Resources Challenge at the IROS 2025 conference in Hangzhou, China 😃

😠💢😵‍💫Tired of endless data collection & fine-tuning every time you try out VLA? Meet RDT2, the first foundation model that zero-shot deploys on any robot arms with unseen scenes, objects & instructions. No collection. No tuning. Just plug and play🚀 Witness a clear sign of embodied superintelligence - 7B one-step diffusion → 23 Hz inference⚡ - Re-designed UMI @chichengcc @SongShuran and manufactured 100 portable devices - Trained on 10K-hour UMI data on 100 real houses - Zero-shot: pick, place, press, wipe… open-vocabulary - Demos: block 30 m/s arrows in 500 ms🛡️; first to play ping-pong with an end-to-end model 🏓; extinguish burning incense by shaking quickly🥢 Fully open source at github.com/thu-ml/RDT2 Project page: rdt-robotics.github.io/rdt2/ Thanks to awesome collaborators @bang_guo96535 @D0g4M74794 @EthanNg51931527

I'm observing a mini Moravec's paradox within robotics: gymnastics that are difficult for humans are much easier for robots than "unsexy" tasks like cooking, cleaning, and assembling. It leads to a cognitive dissonance for people outside the field, "so, robots can parkour & breakdance, but why can't they take care of my dog?" Trust me, I got asked by my parents about this more than you think ... The "Robot Moravec's paradox" also creates the illusion that physical AI capabilities are way more advanced than they truly are. I'm not singling out Unitree, as it applies widely to all recent acrobatic demos in the industry. Here's a simple test: if you set up a wall in front of the side-flipping robot, it will slam into it at full force and make a spectacle. Because it's just overfitting that single reference motion, without any awareness of the surroundings. Here's why the paradox exists: it's much easier to train a "blind gymnast" than a robot that sees and manipulates. The former can be solved entirely in simulation and transferred zero-shot to the real world, while the latter demands extremely realistic rendering, contact physics, and messy real-world object dynamics - none of which can be simulated well. Imagine you can train LLMs not from the internet, but from a purely hand-crafted text console game. Roboticists got lucky. We happen to live in a world where accelerated physics engines are so good that we can get away with impressive acrobatics using literally zero real data. But we haven't yet discovered the same cheat code for general dexterity. Till then, we'll still get questioned by our confused parents.

I want one 🤩

Let me introduce more details about our new quadruped robot, KLEIYN. This robot is capable of chimney climbing on walls of various widths, like Ninja! I will explain its design and learning methodology. Thread👇

DualMap: Online Open-Vocabulary Semantic Mapping for Natural Language Navigation in Dynamic Changing Scenes github.com/Eku127/DualMap >DualMap is an online open-vocabulary mapping system that enables robots to understand and navigate dynamic 3D environments using natural language.

NVlabs/PyCuVSLAM Highly accurate and efficient VSLAM system for Python github.com/NVlabs/PyCuVSLAM > PyCuVSLAM is the official Python wrapper around the cuVSLAM visual-inertial SLAM (Simultaneous Localization And Mapping) software package developed by NVIDIA. It is a highly accurate and computationally efficient package using CUDA acceleration for real-time visual-inertial SLAM.

Documenting lab experiments @SnT_uni_lu #LunaLab #SnT #uni_lu #SpaceR

This announcement is very important for robotic startups. USB is unreliable on real-world product and having a RealSense camera with Power over Ethernet is great! intelrealsense.com/depth-cam…

This is the most amazing thing I saw in the ROS community EVER reddit.com/r/ROS/s/3IuPSFdy1…

Sounds interesting indeed 👀