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.
Jiqizhixin("The heart of the machine") is China's leading cutting-edge technology media and industry service platform, focusing on artificial intelligence, robotics and neurocognitive science, and insisting on providing high-quality content and various industrial services for practitioners.
机器之心是国内领先的前沿科技媒体和产业服务平台,关注人工智能、机器人和神经认知科学,坚持为从业者提供高质量内容和多项产业服务。
- C and C++
- Architecture, Design Patterns and Refactoring
- Skills & Tools
- Agile Software Development and Scrum
- Operating Systems and Networking
- Embedded Systems and Computer Architecture
- Version Control
- Robotics
- Mechanical Engineering
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- 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, and 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.