This course introduces machine learning methods in robotics applications.It is a broad overview of existing methods, motivations and main ideas in the context of pattern recognition. After a short theoretical background, participants will perform simple exercise using open source (usually R)
This course introduces machine learning methods in robotics applications.It is a broad overview of existing methods, motivations and main ideas in the context of pattern recognition. After a short theoretical background, participants will perform simple exercise using open source (usually R) or any other popular software.
Course Outline
Regression
Probabilistic Graphical Models
Boosting
Kernel Methods
Gaussian Processes
Evaluation and Model Selection
Sampling Methods
Clustering
CRFs
Random Forests
IVMs
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Introduction to the design, construction, and control of autonomous mobile robots. This course covers the basic mechanics, electronics, and programming for robotics, and the applications of robots in cognitive science.
WhizKidz has classes for the MakeBlock mBot and a DIY robot based on Arduino.
This course is composed of two parts. During the first three days, participants will be introduced to flying robots, safety, ethics, and regulations. They will understand the components of flying robots and how to control and operate.
This course is centered around 3 mini projects exploring central concepts to robot programming and 1 final project whose topic is chosen by the students. Each of these mini projects will involve students programming real, physical robots interacting with the real world.
At least one year solid coding experience with one of the following programming languages: Python, C++, Java. Good understanding of primitive data types and data structures and control flow.Â
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