Course title
1M9853001
Micro Mechatronics

hasegawa tadahiro Click to show questionnaire result at 2018
Course content
According to a survey by 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. The strategy of design when developing an autonomous mobile robot will be lectured, using a real mobile robot "Beego".
Purpose of class
The design strategy, system design method, various kinds of sensor, and programming skill for reallizing that a mobile robot can move autonomously will be lectured using an educational mobile robot "Beego".
Goals and objectives
  1. Understand the principle and how to use of various sensor that is used in an autonomous mobile robot.
  2. Understand self-localization method that is used in an autonomous mobile robot.
  3. Understand the motion control method that is used in an autonomous mobile robot.
  4. Understand the navigation that is used in an autonomous mobile robot.
Language
English
Class schedule

Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Guidance of lecture and necessary knowledge for this lecture
- Introduction of application example of autonomous mobile robots
- Introduction of educational mobile robot "Beego"
- Overview of programming environment
- Programming technique (C, C++)

Basic mathematics needed for this lecture
- Linear algebra, probability statistics, error analysis, least squares method, coordinate transformation, normal distribution, etc.
Survey of application example of mobile robots 90minutes
Review the mathematics described in the Class schedule 1 90minutes
2. Explain the traveling commands for an autonomous mobile robot
- How to use YPSpur command
- How to implement the above command, and its practice
Review how to implement the travel command 90minutes
3. Practical training using the traveling commands of an autonomous mobile robot
- Autonomous traveling in a global coordinates ( 2 to 3 challenges)
Review of programs that you made 90minutes
4. Practical training for robot middleware using common memory "SSM (Sensor Sharing Manager)" ( 2 to 3 challenges) Review of programs that you made 90minutes
5. Input to an autonomous mobile robot (Internal Sensor)
- How to use encoder, gyro sensor, IMU, etc.
- Self-localization using only an internal sensor for an autonomous mobile robot
Survey of sensors described in the Class schedule 5 90minutes
6. Input to an autonomous mobile robot (External Sensor) #1
- How to use 2D LIDAR
- Practical training using 2D LIDAR (Simple human tracking function)
Survey of sensors described in the Class schedule 6 90minutes
7. Input to an autonomous mobile robot (External Sensor) #2
- Practical training using 2D LIDAR ( Detection of distance and angle against wall )
Review of programs that you made 90minutes
8. Output to an autonomous mobile robot (Velocity, Angular velocity)
- About a motion control
- Practical training how to making the traveling commands that used in Class schedule 2 and 3

Way Point (WP) Navigation for an autonomous mobile robot
- Detecting method when getting to WP
Survey of associated journals about a motion control and WP navigation 90minutes
9. Output to an autonomous mobile robot (Position, Orientation)
- About a self-localization using an external sensor
- About Sensor fusion
Survey of associated journals about self-localization method for an autonomous mobile robot 90minutes
10. Mapping based on self-localization of an autonomous mobile robot
- Occupied grid map using 2D LIDAR
Survey of associated journals about an occupied grid map 90minutes
11. Navigation for an autonomous mobile robot #1
- Self-localization using wheel odometry
Survey of associated journals about navigation 90minutes
12. Navigation for an autonomous mobile robot #2
- Self-localization applying a position correction by a wall detection
- Comparing with navigatoin used in the class schedule 11
Review of programs that you made 90minutes
13. Navigation for an autonomous mobile robot #3
- Self-localization using a scan matching
- Comparing with navigatoin used in the class schedule 12
Survey of associated journals about navigatoin 90minutes
Review of programs that you made 90minutes
14. Presentation and discussion on the autonomous navigation system that each group made. Review of Class schedule 1-13, and survey of associated journals 90minutes
Total. - - 1440minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

report Program code Total.
1. 5% 20% 25%
2. 5% 20% 25%
3. 5% 20% 25%
4. 5% 20% 25%
Total. 20% 80% -
Evaluation method and criteria
report 20%
Program code 80%

total score 60% is required
Textbooks and reference materials
Assign selected papers during lectures
Prerequisites
Basic mathematics ( Linear algebra, probability statistics, error analysis, least squares method, coordinate transformation, normal distribution ) and programming technique are required.
Office hours and How to contact professors for questions
  • Generally, feel free to ask any questions after the class
    Otherwise, please take an appointment by e-mail.
    Simple questions can be answered by e-mail.
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
  • Course that cultivates a basic problem-solving skills
Active-learning course
About half of the classes are interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicatable
N/A N/A
Education related SDGs:the Sustainable Development Goals
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Tue Aug 25 04:07:33 JST 2020