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.
In this class, students will learn how to design an autonomous driving system for a mobile robot, how to estimate the position
and angle of the mobile robot, how to handle various sensors, how to handle various sensors, and how to program to implement
them.
- 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% | 20% | 30% |
| 2. | 10% | 30% | 40% |
| 3. | 10% | 20% | 30% |
| Total. | 30% | 70% | - |
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1． | (Remote Lecture) Guidance for this lecture (Confirming the necessary environment and knowledge for this lecture) - Introduction of the educational mobile robot "Beego" - Check the programming environment - Programming language (C, C++) - Basic mathematics needed for this lecture (Linear algebra, probability statistics, error analysis, least squares method, coordinate transformation, normal distribution, etc.) Introduction of research examples of autonomous mobile robots at Shibaura Institute of Technology |
Review contents of the "Prerequisites" listed in the syllabus | 90minutes |
| Survey of application examples of autonomous mobile robots | 90minutes | ||
| Summarize the ideas discussed in the previous lecture into slides using Miro | 90minutes | ||
| 2． | (Remote Lecture) Prerequisites for programming autonomous driving - About system configuration, coordinate system settings, estimated parameters for autonomous driving, etc. - About middlewares sucha as SSM, ROS, etc. Self-localization method (Wheel odometry) - Theoretical explanations, and the practical training with programming |
Review the program you have created | 90minutes |
| 3． | (Remote Lecture) Presentation and discussion of previous class assignment (wheel odometry) in Miro Self-localization method (Inertial Measurement Unit : IMU) - Theoretical explanations, and the practical training with programming |
Review the program you have created | 90minutes |
| 4． | (Remote Lecture) Presentation and discussion of previous class assignment (IMU) in Miro Self-localization method (Gyro-odometry) - Theoretical explanations, and the practical training with programming Explanation of LIDAR and how to use it - Theoretical explanations, and the practical training with programming |
Review the program you have created | 90minutes |
| 5． | (Remote Lecture) Presentation and discussion of previous class assignment (Gyro-odometry) in Miro Environmental Recognition Using LIDAR - Explaining application examples of environmental recognition - Practical training by programming a wall detection (detecting distance and angle to a wall) |
Review the program you have created | 90minutes |
| 6． | (Remote Lecture) Presentation and discussion of previous class assignment (LiDAR) in Miro Self-localization method (Scan matching) - Explanation about the scan matching method such as particle filters, etc. - Practical training with programming |
Review the program you have created | 90minutes |
| 7． | (Remote Lecture) Presentation and discussion of previous class assignment (Scan matching) in Miro Considering applications using autonomous mobile robots - Propose an idea and consider how to implement it - Summarize your ideas into slides using Miro Presentation and discussion on autonomous mobile robots that each group proposed. - Presentation using slides created in Miro |
Review of Class schedule 1-6, and survey of associated journals | 90minutes |
| 8． | - | - | 0minutes |
| 9． | - | - | 0minutes |
| 10． | - | - | 0minutes |
| 11． | - | - | 0minutes |
| 12． | - | - | 0minutes |
| 13． | - | - | 0minutes |
| 14． | - | - | 0minutes |
| Total. | - | - | 810minutes |
<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 (thase@shibaura-it.ac.jp).
- Simple questions can be answered by e-mail (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 01 04:32:56 JST 2024