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Behavioral and cognitive robotics

Course name: Behavioral and cognitive robotics
Course number: R-11
Area of instruction: Computer Science and Engineering

Administrative details

Faculty: Computer Science and Engineering
Year of instruction: 4th year of BSc
Semester of instruction: Spring semester
No. of Credits: 5 ECTS
Total workload on average: 180 hours overall
Frontal lecture hours: 2 hours per visit.
Frontal tutorial hours: 0 hours per week.
Lab hours: 2 hours per visit.
Individual lab hours: 0 hours per week.
Frequency: three 6 sessions though-out the semester.
Grading mode: letters: A, B, C, D.

Course outline

This is an introductory course in behavioral and cognitive robotics. During the course, students will learn the fundamental principles of robotics with particular reference to autonomous robotics: embodiment and situatedness, morphological computation, sensory-motor coordination, integration of information through time, the dynamical system nature of behavior and cognition, compositionality and generalization. Moreover, students will learn how to program robots and how to design robots that develop their behavioral and cognitive skills autonomously, in interaction with the environment, through an evolutionary and/or learning algorithms. This will be realized through the illustration of concrete examples taken from state of the art research in the field and through practical experimentation carried in simulation.

Expected learning outcomes

The course will provide an opportunity for participants to:

Understand the fundamental principle characterizing autonomous robots
Become familiar evolutionary and learning methods for continuous control optimization
Understand the research trends and the open problems in the field

Required background knowledge

Programming skills in C++ and Python. Knowledge on neural network and machine learning would help but are not mandatory

Prerequisite courses

None

Detailed topics covered in the course

Braitenberg’s vehicles
Embodiment, Situatedness, Behaviors integration and coordination
Collective and Swarm Robotics
Evolutionary Algorithms
Reinforcement Learning

Reference material

None

Required computer resources

Students will need to run computer experiments on a laptop and/or on lab computers. The access to a computer cluster for running computational expensive experiments would be helpful.

Students will be required to use and modify a software tool written in Python and C/C++ which run on multiple platforms (Linux, Microsoft Windows, and Mac OS). The tool requires freely available software libraries (C compiler, QT and GSL/GNU libraries).

Evaluation

Assignments (20%)
Interim Project Report (20%)
Final Project Report (60%)

MSc:BehavioralAndCognitiveRobotics old

Contents