Nybble makes programming and robotics fun to learn and understand, all in on | Check out 'Nybble - World's Cutest Open Source Robotic Kitten' on Indiegogo.
It is a research group under the Stanford Vision & Learning Lab that focuses on developing methods and mechanisms for generalizable robot perception and control.
We work on challenging open problems at the intersection of computer vision, machine learning, and robotics. We develop algorithms and systems that unify in reinforcement learning, control theoretic modeling, and 2D/3D visual scene understanding to teach robots to perceive and to interact with the physical world.
Researchers at Siemens Corporate Technology in Berkeley, CA, have developed a set of gears to test different robot learning approaches to assembly. If you want to benchmark your robot learning algorithms and apply them to a challenging problem, 3D print the gears and share your results with us!
A collection of .BLEND and .FBX files to accompany the Robotic Design with Blender tutorial series on YouTube:(Part 1) https://youtu.be/aRBHMRa6pIA(Part 2) https://youtu.be/TKc-g84j2x8(Part 3) https://youtu.be/Cuo_ytkvCpo(Part
The Robotics and Autonomous Systems Group at CSIRO Data 61 develops foundational and applied research for a broad range of domains including; agriculture, advanced manufacturing, mining, biodiversity and biosecurity, environmental research and monitoring, cultural heritage and online learning.
- Modern C++ for Computer Vision
- 3D Coordinate Systems
- Photogrammetry I
- Mobile Sensing and Robotics I
- Photogrammetry II
- Mobile Sensing and Robotics II
- Techniques for Self-Driving Cars
- Master Project
J. Solà, J. Deray, und D. Atchuthan. (2018)cite arxiv:1812.01537Comment: 17 pages, 12 figures, 7 boxed examples, 193 numbered equations. V2 add chapter with a application examples. V3 fix biblio error and remove the reference to a not-yet-published library in C++. V4 add again the reference to the C++ library "manif", which is made available with this version 4. V5 fix formulas (163) and (179). V6, V7 fix typos. V8 fix sign in eq 149.