354-0644/01 – Localization, Navigation and Mapping (LNaTM)

Gurantor department	Department of Robotics	Credits	4
Subject guarantor	doc. Ing. Tomáš Kot, Ph.D.	Subject version guarantor	doc. Ing. Tomáš Kot, Ph.D.
Study level	undergraduate or graduate	Requirement	Compulsory
Year	2	Semester	winter
		Study language	Czech
Year of introduction	2021/2022	Year of cancellation
Intended for the faculties	FS	Intended for study types	Follow-up Master

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
BOB0001	prof. Ing. Zdenko Bobovský, PhD.
GRU0037	Ing. Stefan Grushko, Ph.D.
KOT19	doc. Ing. Tomáš Kot, Ph.D.
OSC0011	Ing. Petr Oščádal, Ph.D.

Extent of instruction for forms of study
Form of study	Way of compl.	Extent
Full-time	Graded credit	2+2

Subject aims expressed by acquired skills and competences

The graduate of the course will gain an overview of navigation, localization and map creation in robotic systems. He / she acquires knowledge needed for map creation, map localization and navigation in a map.

Teaching methods

Lectures
Tutorials
Project work

Summary

Localization, navigation and mapping is an important task of service mobile robotic systems. Students will learn how to create maps of the environment, determine the position of systems based on sensor data and map knowledge and plan movement in this environment.

Compulsory literature:

[1] Kolski, S.. Mobile robots: perception & navigation. Mammendorf : Pro literatur, 2007. ISBN: 3-86611-283-1 [2] Mukhopadhyay, S. C. and Gupta, G. S.. Autonomous robots and agents. Berlin : Springer, 2010. ISBN 978-3-540-73424-6 [3] Lentin J. Cacace J.. Mastering ROS for robotics programming: design, build, and simulate complex robots using the Robot Operating System. Birmingham : Packt, 2018. ISBN 978-1788478953 [4] Koubaa, A.. Robot Operating System (ROS) The Complete Reference (Volume 3). s.l. : Springer-Verlag, 2019. ISBN 978-3-319-91590-6 [5] Koubaa, A.. Robot path planning and cooperation: foundations, algorithms and experimentations. S.l. : SPRINGER, 2019, ISBN 978-3-319-77042-0

Recommended literature:

[1] Savkin A., Matveev A., Hoy M., Wang Ch.. Safe robot navigation among moving and steady obstacles. Oxford: Elsevier butterworth-hein, 2016. ISBN: 9780128037300 [2] Barrera, A.. Mobile robots navigation. SL : Sciyo.com, 2010. ISBN: 978-953-307-076-6 [3] Fehlman, W. L.. Mobile robot navigation with intelligent infrared image interpretation. Springer, 2014. ISBN 978-1-84882-509-3

Way of continuous check of knowledge in the course of semester

Continuous check and point evaluation of exercise results. The result is a semestral project.

E-learning

Other requirements

There are no additional requirements for the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Basic concepts 2. Sensors in mobile robotics 3. Detection of key features using sensors 4. Map representation 5. Localization - introduction, meaning, uncertainty 6. Localisation methods I 7. Localization methods II 8. Automatic mapping (SLAM) 9. Navigation and trajectory planning 10. Trajectory planning methods I 11. Trajectory planning methods II 12. Trajectory planning methods III 13. Dynamic obstacle avoidance 14. Current trends

Conditions for subject completion

Full-time form (validity from: 2021/2022 Winter semester)

Task name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Graded credit	Graded credit	100	51	3

Valid from	Valid until	Mandatory attendence participation
Sep 7, 2019 6:43:33 AM	Aug 1, 2023 9:44:03 AM	An attendance on the seminars is minimum 80%.

Mandatory attendence participation: In order to complete the credit, the student must submit semester projects as specified by the supervisor. Compulsory participation in the exercise is 80 %.

Show history

Conditions for subject completion and attendance at the exercises within ISP: In order to complete the credit, the student must submit semester projects as specified by the supervisor. Compulsory participation in the exercise is 80 %.

Show history

Occurrence in study plans

Academic year	Programme	Branch/spec.	Form	Study language	Tut. centre	Year	Type of duty
2024/2025	(N0719A270009) Robotics	(S03) Service Robotics	P	Czech	Ostrava	2	Compulsory	study plan
2023/2024	(N0719A270009) Robotics	(S03) Service Robotics	P	Czech	Ostrava	2	Compulsory	study plan
2022/2023	(N0719A270009) Robotics	(S03) Service Robotics	P	Czech	Ostrava	2	Compulsory	study plan
2021/2022	(N0719A270009) Robotics	(S03) Service Robotics	P	Czech	Ostrava	2	Compulsory	study plan

Occurrence in special blocks

Block name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner

Assessment of instruction

2023/2024 Winter