Explores motor control systems, covering algorithms, sensor integration, and practical applications in robotics and automation.
Explores transporters as a practical alternative to parallel transport, discussing minimal requirements, examples with matrices, pragmatic choices, and optimization algorithms.
On Convex Optimization covers course organization, mathematical optimization problems, solution concepts, and optimization methods.
Explores dataflow analysis for optimization, including equations solving, live variables, reaching definitions, and very busy expressions.
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Covers the Simplex algorithm for function minimization with linear constraints.
