Checking date: 14/02/2022

Course: 2022/2023

Intelligent decision-making in robotics
Study: Bachelor in Robotics Engineering (381)

Coordinating teacher:

Department assigned to the subject: Department of Systems Engineering and Automation

Type: Compulsory
ECTS Credits: 3.0 ECTS


Skills and learning outcomes
Description of contents: programme
1. Introduction: autonomy in robotics, common terms, examples of applications, high-level vs. low-level decisions 2. Robotics paradigms: hierarchical, reactive, deliberative, hybrid 3. Dynamic Programming 4. Utility and Decision Theory 5. Game Theory 6. Probabilistic methods (Kalman filters, Particle filters, HMM, Dynamic Bayesian networks, POMDPs) 7. Reinforcement Learning 8. Bio-inspired Decision Making Systems
Learning activities and methodology
THEORETICAL PRACTICAL CLASSES. Knowledge and concepts students must acquire. Receive course notes and will have basic reference texts. Students partake in exercises to resolve practical problems. TUTORING SESSIONS. Individualized attendance (individual tutoring) or in-group (group tutoring) for students with a teacher. Subjects with 6 credits have 4 hours of tutoring/ 100% on- site attendance. STUDENT INDIVIDUAL WORK OR GROUP WORK. Subjects with 6 credits have 98 hours/0% on-site. WORKSHOPS AND LABORATORY SESSIONS. Subjects with 3 credits have 4 hours with 100% on-site instruction. Subjects with 6 credits have 8 hours/100% on-site instruction.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

The course syllabus may change due academic events or other reasons.