To be able to design behaviour-based control architectures to solve robotic tasks. To be able to analyse deliberative control architectures. To be able to apply basic Reinforcement Learning algorithms to learn basic robot behaviours. To be able to apply path planning algorithms
1. Overview of Control Architectures 2. Behaviour-based architectures 3. Path Planning 3.1. Bug algorithms 3.2. Configuration space 3.3. Potential functions 3.4. Topological maps 3.5. Graph search 3.6. Cell decompositions 3.7. Sampling-based algorithms
Tipus d’activitat Hores amb professor Hores sense professor Total Elaboració individual de treballs 10,00 28,00 38,00 Prova d'avaluació 4,00 12,00 16,00 Sessió expositiva 20,00 15,00 35,00 Sessió pràctica 12,00 24,00 36,00 Total 46,00 79,00 125
Arkin (1998). Bahavior-based Robotics. MIT Press. Catàleg Choset, Howie M. (2005). Principles of robot motion : theory, algorithms, and implementation . Cambridge, Massachusetts : MIT Press. Catàleg Sutton, Richard S., Barto, Andrew G. (cop. 1998). Reinforcement learning : an introduction. Cambridge, Mass.: MIT Press. Catàleg
Activitats d'avaluació: Descripció de l'activitat Avaluació de l'activitat % Laboratory Practical exercices in the laboratory. 30 Project A project will be proposed to be accomplished by a team of students. Project will require implementation of AR algorithms. A final presentation will be done by students. 40 Final Exam Theoretical and practical contents will be evaluated in the final exam. 30