In this course, students will understand the principles and usage of various sensors required for autonomous navigation of
mobile robots, as well as the fundamentals of system design.
Students will also acquire programming skills for implementing autonomous driving systems.
Students will also acquire programming skills for implementing autonomous driving systems.
According to a survey by the New Energy and Industrial Technology Development Organization (NEDO), the market for service
robots, including autonomous mobile robots, is expected to expand to nearly 10 trillion yen by 2035. Recently, autonomous
mobile robots have been introduced into urban areas, commercial facilities, airports, hotels and so on. In this class, autonomous
driving systems for mobile robots will be explained. In particular, the class will focus on the self-localization method,
which is one of the key elements to realize autonomous driving systems, and the lecture and hands-on practice will be given.
- The students will be able to understand the principle and how to use of various sensor that is used in an autonomous mobile robot.
- The students will be able to understand self-localization method that is used in an autonomous mobile robot.
- The students can program self-localization algorithms that is used in an autonomous mobile robot.
| Presentation | Program code | Total. | |
|---|---|---|---|
| 1. | 10% | 10% | |
| 2. | 10% | 10% | |
| 3. | 10% | 70% | 80% |
| Total. | 30% | 70% | - |
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1． | (Online class) Course guidance (confirmation of the environment and prerequisite knowledge required for this course) - About this course - Basic knowledge of autonomous mobile robots and self-localization - Confirmation of the programming environment (C, C++) and required fundamental mathematical knowledge (linear algebra, probability and statistics, error analysis, least squares method, coordinate transformations, normal distribution, etc.) |
Review the contents of the ”Prerequisites” listed in the syllabus | 100minutes |
| Become familiar with how to use the online whiteboard Miro | 30minutes | ||
| 2． | (Online class) The robot targeted in this course and its motion Wheel odometry - Explanation of the method and its implementation - Programming exercise |
Ensure that the programs for this course run properly in advance | 100minutes |
| Complete the program and summarize the execution results on Miro | 100minutes | ||
| 3． | (Online class) Presentation and explanation of the previous assignment (wheel odometry) Attitude estimation using IMU - Explanation of the method and its implementation - Programming exercise |
Review the program from the previous lecture | 100minutes |
| Complete the program and summarize the execution results on Miro | 100minutes | ||
| 4． | (Online class) Presentation and explanation of the previous assignment (IMU) Gyro odometry - Explanation of the method and its implementation - Programming exercise Basics of LiDAR - Explanation of the fundamentals of LiDAR and its basic usage - Programming exercise |
Review the program from the previous lecture | 100minutes |
| Complete the program and summarize the execution results on Miro | 100minutes | ||
| 5． | (Online class) Presentation and explanation of the previous assignment (gyro odometry and LiDAR) Environment perception using LiDAR - Explanation of the wall detection method using LiDAR and its implementation - Programming exercise |
Review the program from the previous lecture | 100minutes |
| Complete the program and summarize the execution results on Miro | 100minutes | ||
| 6． | (Online class) Presentation and explanation of the previous assignment (wall detection using LiDAR) Scan matching and particle filter - Explanation of the method and its implementation - Programming exercise |
Review the program from the previous lecture | 100minutes |
| Complete the program and summarize the execution results on Miro | 100minutes | ||
| 7． | (Online class) Presentation and explanation of the previous assignment (scan matching and particle filter) Review through a poster tour - Creation of posters summarizing each method (Miro slides) - Presentations using the posters |
Review the program from the previous lecture | 100minutes |
| Review the content covered in Lectures 1–6 | 100minutes | ||
| 8． | - | - | 0minutes |
| 9． | - | - | 0minutes |
| 10． | - | - | 0minutes |
| 11． | - | - | 0minutes |
| 12． | - | - | 0minutes |
| 13． | - | - | 0minutes |
| 14． | - | - | 0minutes |
| Total. | - | - | 1330minutes |
＜Criteria＞
Presentation : 30%
Programming : 70%
＜evaluation method＞
To pass the class must earn a total score of more than 60%.
The 60% level indicates that the student can understand how to estimate the self-position and angle of a mobile robot and can realize its simulation.
Presentation : 30%
Programming : 70%
＜evaluation method＞
To pass the class must earn a total score of more than 60%.
The 60% level indicates that the student can understand how to estimate the self-position and angle of a mobile robot and can realize its simulation.
| ways of feedback | specific contents about "Other" |
|---|---|
| Feedback in the class |
Academic journal papers related to autonomous mobile robots will be handed out during lectures.
1) Can prepare for an equipment that allows you to take distant lectures (remote lectures) on your own.
2) [Important] Can prepare for a C++ programming environment on your own.
*With OS, Ubuntu is best, but Windows and Mac are also acceptable.
3) Basic knowledge for mathematics (linear algebra, probability and statistics, error analysis, least squares method, coordinate transformation, etc.) is required.
4) Basic knowledge for programming techniques (C and C++) is required
2) [Important] Can prepare for a C++ programming environment on your own.
*With OS, Ubuntu is best, but Windows and Mac are also acceptable.
3) Basic knowledge for mathematics (linear algebra, probability and statistics, error analysis, least squares method, coordinate transformation, etc.) is required.
4) Basic knowledge for programming techniques (C and C++) is required
- Generally, feel free to ask any questions after the lecture
- Otherwise, please take an appointment by e-mail (r-yajima@shibaura-it.ac.jp, thase@shibaura-it.ac.jp).
- Simple questions can be answered by e-mail (r-yajima@shibaura-it.ac.jp, thase@shibaura-it.ac.jp).
- Course that cultivates an ability for utilizing knowledge
- Course that cultivates a basic problem-solving skills
| Work experience | Work experience and relevance to the course content if applicable |
|---|---|
| N/A | N/A |
Last modified : Fri Mar 20 04:04:22 JST 2026