AME551

This course presents the foundations of autonomous robot control. The course presents classical approaches to path planning (road maps, cell decomposition, artificial potentials, graph search), heuristic algorithms (Tabu search, genetic algorithms, and ant-colony optimization), and probabilistic methods. The course also includes an introduction to common robotic systems, their kinematic and dynamic models using Lagrangian and Euler-Newton formulations. Examples of dynamics of rigid bodies, and constrained models of uni- and bi-cycle rovers are presented. In the final part of the class, the path planning algorithms and robot models are used to demonstrate the design of timing laws (trajectory planning) and examples of closed-loop robot control.

018378

Fall