Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Upon completion of this course, the student will be able to design a comprehensive, high-level architecture for a mobile robotic system capable of addressing diverse challenges in the domain of field, indoor, service, agricultural robotics and similar, as well as address some challenges in the field of and autonomous vehicles.

This proficiency will encompass the ability to:

  • Identify and name the primary challenges encountered by mobile robots in their respective fields and propose effective solutions.
  • Illustrate the composition of a robotic system well-suited to the specific problem, involving the selection of appropriate subsystem instances. The student will be able to present the interplay between these subsystems, utilizing accurate terminology.
  • Assess, select, and, to a limited extent, apply and implement fundamental methodologies and algorithms relevant to the identified challenges.

Credits: 5

Schedule: 25.02.2025 - 28.05.2025

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Arto Visala, Tomasz Kucner

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    • Robotic locomotion
    • Sensing and perception
    • Mapping and localisation (Probabilistic approach)
    • Contemporary software tools for robotics
    • Simultaneous Localisation and mapping
    • Inertial Navigation systems
    • Global Navigation Satelite systems
    • Task Planning
    • Motion Planning
    • Control

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Group Work, Quizzes, Final Examination

Workload
  • valid for whole curriculum period:

    • Lectures
    • Working at home with lecture material
    • Group Work - conceptual work
    • Group Work - practical work

DETAILS

Study Material
  • valid for whole curriculum period:

    • Lectures and all other material in Mycourses. 
    • Alonzo Kelly, CMU, Mobile Robotics: Mathematics Models and Methods, Cambridge University Press, 2014; 
    • Trun & al, Probabilistic robotics, MIT Press 2005; 
    • Siegwart, Nourbakhsh, Introduction to Autonomous Mobile Robots, MIT Press (2nd ed.)

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Spring IV - V
    2025-2026 Spring IV - V