Mobile Robotics

Course Description

General considerations regarding mobile robots: basic terms, definitions, classifications, historical development, applications and examples of mobile robots. Mobile robots hardware: drive mechanisms, actuators, sensors, control circuits. Non-visual and visual perception sensors. Robot sensor signals processing and interpretation. Multiple sensors information fusion in order to improve quality and robustness of robots navigation through space. Control and navigation system structures. Methods and algorithms of control and navigation system for obstacle avoidance, unknown space exploration, map building, localization and path planning for mobile robots. Introduction to self learning mobile robots and human-robot communication. Basics of coordinated work of multiple autonomous mobile robots.

General Competencies

Students master the main principles of mobile robotics and gain basic knowledge for design and development of mobile robots control and navigation systems.

Learning Outcomes

  1. clasify mobile robots according to various criteria
  2. analyze driving mehanisms and sensor system sutable for intended application
  3. assembly sensors and actuators with the embedded computer system on mobile robot
  4. develop sensor fusion algorithms
  5. develop motion planning algorithms
  6. develop motion of mobile robots localization
  7. develop algorithms of environment 2D map building

Forms of Teaching

Lectures

Lectures are organized in two cycles.

Laboratory Work

Students work five laboratory exercises (LE) on LEGO mobile robots - each LV lasts three hours : • LE1: Odometry calibration of a mobile robot • LE2: Occupancy grid map building by applying Bayes rule • LE3: Mobile robot localization by Kalman filter and sonars • LE4: Path planning of a mobile robot • LE5: Path following and obstacle avoidance

Consultations

Upon request.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 50 % 20 % 50 % 20 %
Mid Term Exam: Written 50 % 30 % 0 %
Final Exam: Written 50 % 30 %
Final Exam: Oral 20 %
Exam: Written 50 % 60 %
Exam: Oral 20 %
Comment:

All five laboratory exercises are obligatory.

Week by Week Schedule

  1. General considerations regarding mobile robots: basic terms, definitions, classifications, historical development, applications and examples of mobile robots.
  2. Mobile robots hardware, drive mechanisms, actuators. Mobile robots locomotion.
  3. Mobile robots kinematics.
  4. Proprioceptive and non-visual perceptive sensors for mobile robots.
  5. Visual perceptive sensors for mobile robots.
  6. Processing and interpretation of robots sensors signals. Measurement uncertainty.
  7. Multiple sensors information fusion in order to improve quality and robustness of robots navigation through space.
  8. Midterm exam.
  9. Control and navigation system structures.
  10. Algorithms for global path planning of mobile robot in space.
  11. Algorithms for obstacle avoidance and global path following.
  12. Robots relative and absolute localization in space.
  13. Environment modeling: occupancy grid maps, geometrical properties maps, topological maps, hybrid maps.
  14. Introduction to self-learning mobile robots and human-robot communication. Basics of coordinated work of multiple autonomous mobile robots.
  15. Final exam.

Study Programmes

University graduate
Control Engineering and Automation (profile)
Specialization Course (3. semester)

Literature

Ivan Petrović (2010.), Mobilna robotika - predavanja, FER - Zavod za APR
Roland Siegwart, Illah Nourbakhsh and Davide Scaramuzza (2011.), Introduction to Autonomous Mobile Robots, The MIT Press
Gregory Dudek and Michael Jenkin (2000.), Computational Principles of Mobile Robots, Cambridge University Press

Laboratory exercises

General

ID 127565
  Winter semester
4 ECTS
L1 English Level
L1 e-Learning
30 Lectures
0 Exercises
15 Laboratory exercises
0 Project laboratory

Grading System

87,5 Excellent
75 Very Good
62,5 Good
50 Acceptable