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

clasify mobile robots according to various criteria
analyze driving mehanisms and sensor system sutable for intended application
assembly sensors and actuators with the embedded computer system on mobile robot
develop sensor fusion algorithms
develop motion planning algorithms
develop motion of mobile robots localization
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

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