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

The student understands and can explain main concepts related to Autonomous  mobile robots and vehicles. The student can implement algorithms for different functions of mobile robots.

Credits: 5

Schedule: 27.02.2024 - 29.05.2024

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:

    The locomotion and kinematics of mobile robots and intelligent vehicles. Machine perception and sensors for mobile robots; representing uncertainty, wheel/motor/heading sensors, inertial measurement unit (IMU), beacons, active ranging and machine vision for outdoor use. Mobile robot localization and mapping, probabilistic and other map representations, different approaches for SLAM. Path and trajectory planning and navigation, reactive control, obstacle avoidance and safety. Motion Control; trajectory and path following, NMPC. Intelligent autonomous heavy duty work machines and vehicles. Fleet control. Autonomous cars.

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 : 2022-2023 Spring IV - V
    2023-2024 Spring IV - V

    Enrollment :

    Registration for Courses on Sisu (sisu.aalto.fi).