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1.7× faster inverse kinematics in pure Python, GPU-accelerated! Fully open-source and built for scale [📍Bookmark for later] PyRoki, a modular toolkit for robot kinematic optimization, supporting - inverse kinematics - trajectory optimization, and - motion retargeting. Built for flexibility, but also fast: ✅ Runs on CPU, GPU, and TPU...

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Ilir Aliu - eu/acc

11,881 subscribers

18,358 Aufrufe • vor 1 Jahr •via X (Twitter)

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5 Kommentare

Profilbild von Lukas Die Kunst
Lukas Die Kunstvor 1 Jahr

PyRoki’s 1.7× IK speedup with Python-native GPU support is an engineering milestone. Already testing this for UAV trajectory optimization—exactly what we needed for real-time swarm coordination.

Profilbild von Page to Pixel Publishing
Page to Pixel Publishingvor 2 Jahren

The Art of Flight is a homage to 80s/90s arcade action shmups with a fresh twist on the genre. Pilot multiple ships at the same time to take on oncoming waves of enemies in this fast paced space shooter. Wishlist on Steam today!

Profilbild von Mykhailo Sorochuk
Mykhailo Sorochukvor 1 Jahr

Looks impressive! Excited to see how it performs in real-world applications.

Profilbild von Octoberhung
Octoberhungvor 1 Jahr

import pyroki_snippets as pks, and ModuleNotFoundError: No module named 'pyroki_snippets'

Profilbild von Dhananjay rajmane
Dhananjay rajmanevor 1 Jahr

Is it working for quadruped robot?

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Arc

772,297 Aufrufe • vor 11 Monaten

Awesome Robotics! 💾 Building your own robot just got a lot easier. MathWorks have released an open-source GitHub repository packed with robotics resources for anyone interested in getting hands-on. The repo includes examples for robot arms, ground vehicles, and drones, with projects that show how to connect with ROS and ROS2 or even deploy Simulink models directly as ROS nodes. There are also more advanced demos, like modeling off-road environments and testing navigation algorithms in photorealistic simulations. Everything is well-documented, with tutorials and links that make it easy to go from concept to prototype. 📑 Whether you’re a student, researcher, or just curious, there’s material here for every level. And since it’s an open community project, you can not only explore but also share your own contributions. For anyone looking to learn robotics by doing, this is a solid place to start! Here’s the link: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Awesome Robotics! 💾 Building your own robot just got a lot easier. MathWorks have released an open-source GitHub repository packed with robotics resources for anyone interested in getting hands-on. The repo includes examples for robot arms, ground vehicles, and drones, with projects that show how to connect with ROS and ROS2 or even deploy Simulink models directly as ROS nodes. There are also more advanced demos, like modeling off-road environments and testing navigation algorithms in photorealistic simulations. Everything is well-documented, with tutorials and links that make it easy to go from concept to prototype. 📑 Whether you’re a student, researcher, or just curious, there’s material here for every level. And since it’s an open community project, you can not only explore but also share your own contributions. For anyone looking to learn robotics by doing, this is a solid place to start! Here’s the link: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

58,829 Aufrufe • vor 2 Monaten

What if robots could learn real-world tasks from your perspective… without ever touching a robot? This is a system that trains robot policies using nothing but human-first, egocentric video data from smart glasses. No robots, no teleop, no sensors, just humans doing real tasks in the real world. Why it matters ✅ Learns robot policies from 20 minutes of human video; zero robot demos ✅ Generalizes to new objects, views, and even robot morphologies ✅ Uses 3D points for interpretable, spatially grounded learning ✅ Deploys directly to real-world robots with strong zero-shot success Thank you, Vincent Liu, for sharing!!! Learn more here: 🔗 Paper: 🌐 Website: 📍 BOOKMARK FOR LATER
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What if robots could learn real-world tasks from your perspective… without ever touching a robot? This is a system that trains robot policies using nothing but human-first, egocentric video data from smart glasses. No robots, no teleop, no sensors, just humans doing real tasks in the real world. Why it matters ✅ Learns robot policies from 20 minutes of human video; zero robot demos ✅ Generalizes to new objects, views, and even robot morphologies ✅ Uses 3D points for interpretable, spatially grounded learning ✅ Deploys directly to real-world robots with strong zero-shot success Thank you, Vincent Liu, for sharing!!! Learn more here: 🔗 Paper: 🌐 Website: 📍 BOOKMARK FOR LATER

Ilir Aliu - eu/acc

10,509 Aufrufe • vor 1 Jahr