Trajectory Generation: Basics and Profiles

Related lectures (31)

Page 3 of 4

Covers advanced numerical analysis topics including deep neural networks and optimization methods.

Explores polynomial interpolation theory, emphasizing error expression and piecewise definition.

Covers the least squares method for approximating data and handling errors.

Covers the basics of robot simulation and programming using Webots.

Covers the concept of piecewise linear interpolation and the importance of dividing intervals correctly.

Explores obstacle avoidance using Dynamical Systems for robots, focusing on modulation, stability guarantees, and contraction theory.

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Delves into the definition and capabilities of robots based on various sources.

Explores Lagrange interpolation for polynomial construction and introduces the definite integral.

Explores Lagrange interpolation, emphasizing uniqueness and simplicity in reconstructing functions from limited values.