Advanced Robotics | CS 287, UC Berkeley
Comprehensive course on cutting-edge robotics techniques, including probabilistic methods, mapping, localization, and optimal control. Suitable for graduate students and advanced undergraduates.
Introduction
CS287 is an advanced course on robotics, covering topics such as probabilistic robotics, mapping, localization, Kalman filtering, and optimal control. The course provides a comprehensive overview of cutting-edge techniques in robotics and is designed for graduate students and advanced undergraduates.
Highlights
- Covers a wide range of topics in advanced robotics, including probabilistic techniques, mapping, localization, and optimal control
- Includes in-depth discussions of algorithms such as Kalman filtering, Rao-Blackwellized particle filters, and differential dynamic programming
- Features guest lectures from renowned experts in the field of robotics
- Provides hands-on experience through programming assignments and projects
Recommendation
This course is highly recommended for students interested in robotics, artificial intelligence, and control systems. It provides a strong foundation in the theoretical and practical aspects of advanced robotics, and is suitable for both graduate students and advanced undergraduates with a background in computer science, engineering, or a related field.
How GetVM Works
Learn by Doing from Your Browser Sidebar
Access from Browser Sidebar
Simply install the browser extension and click to launch GetVM directly from your sidebar.
Select Your Playground
Choose your OS, IDE, or app from our playground library and launch it instantly.
Learn and Practice Side-by-Side
Practice within the VM while following tutorials or videos side-by-side. Save your work with Pro for easy continuity.