Department of Integrated Science and Engineering Robotics and Artificial Intelligence Course
Based on robotics and the latest AI Gained practical knowledge We develop engineers
Department of Integrated Science and Engineering Robotics and Artificial Intelligence Course Close-UP
Practical learning education with emphasis on experiments and training Based on the foundations of robotics and artificial intelligence, students will acquire knowledge in various fields such as medicine, biology, information, machinery, and aviation, aiming to develop talented individuals with a broad perspective and strong imagination.
カリキュラム
Students will study an efficient curriculum that prepares them for careers in robotics, intelligent robotics, electrical and electronic engineering, and informatics-related fields such as manufacturing, information and communications, and research institutes.
Electronics Experiment The goal of this class is to acquire basic knowledge of electrical circuits and control circuit systems that electronics engineers should be familiar with. Through circuit construction and measurement, students will learn to read and build electrical circuit diagrams, understand the structure and basic functions of microcontrollers, and understand the principles and usage of various sensors. The assignments for the class, including the creation of electrical circuit diagrams, hardware, and software, as well as the measurement of each component, will be tackled as group work.
Robot and Mechatronics Experiments In this class, students will learn the operating principles of various sensors and tackle applied problems that utilize them. They will also learn how to use peripheral electrical and electronic circuits and microcomputers, and acquire practical basic skills. In order to solve problems that they have set themselves, students will design, build, and give a presentation on robots, honing their overall robot building skills.
Robotics and AI experiments This program applies robotics and AI to create an autonomous mobile robot. Students will learn how to build an environmental map using SLAM, self-localization, and navigation to achieve autonomous driving. Students will also learn how to annotate captured images to create a dataset, and how to train, verify, and evaluate a general object recognition model. By integrating these, students will search for target objects while moving autonomously in a complex environment. Through experiments, students will develop the ability to build intelligent robots.
Electronic Circuit Analog electronic circuits that make up electronic devices can be used for a variety of applications if you understand the basics and important points. Therefore, after lecturing on the concepts of basic amplifier circuits and equivalent circuits, which are essential for understanding analog electronic circuits, we will explain analog electronic circuits that can be used for a variety of applications. Specifically, you will learn about transistor amplifier circuits, operational amplifiers, and oscillator circuits, which are the basis of analog circuit design, and also about high-frequency-specific theories (distributed constant circuits) and measurement techniques.
Robot Control In robot control, students learn how to derive equations of motion, estimate unknown parameters, design controllers, and verify them through simulations using actual robots, such as the angle control of a horizontally installed single-axis arm or the position control of a motor-driven four-wheeled cart, to understand basic design methods for controlling robots. This allows students to understand how to apply theory to real machines and to acquire application skills.
artificial intelligence You will learn various ways of thinking and techniques for creating artificial intelligence (AI). You will learn about a wide range of intelligent information processing techniques, from classical AI based on knowledge representation and inference, search, and symbol manipulation, to game AI, genetic algorithms, fuzzy logic, neural networks, and deep learning techniques. Through these, you will acquire the ability to understand and apply AI. You will also develop the ability to research the latest technology and explain it to others, and the ability to think for yourself about the relationship between humans, society, and AI.
成績評価と単位認定
Grading Criteria
About our GPA System
The purpose of introducing the GPA (Grade Point Average) system is to 1. create a unified standard for the faculty, 2. create a standard with excellent fairness, and 3. create a standard that is internationally accepted, and to evaluate the results of learning with an objective numerical value called GPA. This system is roughly based on the grading system adopted by many universities overseas, and is an internationalized grading system that serves as an indicator of academic ability when studying abroad, advancing to Graduate School overseas, or finding employment at a foreign company.
Display of Grades and Assessment Criteria
Classification
Grading Criteria
GPA
Grading Criteria
Details of Assessment
Pass
S.
4.0
90 percent or higher
Represents particularly excellent grades.
A
3.0
80 percent
Represents excellent grades
B.
2.0
70 percent
Represents grades recognized as adequate.
C.
1.0
60 percent
Represents the minimum grade acceptable as a pass.
Fail
D.
0.0
59 points or less
Represents that students have not reached the minimum grades acceptable as a pass
absence
0.0
Missing the exam
Represents that students have not taken the exam for the class or have not submitted a report, etc.
Unqualified
0.0
Not eligible to take the exam
Represents that students are not eligible to take the exam due to insufficient attendance at the class or have abandoned the course.
GPA Calculation Method
*1 GPA will be rounded off to the third decimal place and expressed as a number with two decimal places.
*2 When a student retakes a failed course (fail, absent, or not qualified) and receives a pass grade, or when a student retakes a course and receives a fail grade (fail, absent, or not qualified), the grade before the retake is not included in the GPA. Qualification-related courses are excluded from the "total number of registered credits."
*3 It is desirable to have a GPA of 2.4 or higher (2.2 or higher for Department of Integrated Science and Engineering).
Credit Recognition
To earn credits
Credit system University classes are taught on a credit system. The number of credits is determined based on the number of study hours, and one credit is set at 45 hours of study (of which class time is generally 15 to 45 hours) taking into account the teaching method, educational effect of the class, and necessary study outside of class time. For specific details, please refer to the number of credits listed in the "Course Table."
Earning credits Credits can be earned by registering for classes at the beginning of each semester, attending classes, completing the necessary preparatory studies, and passing exams. University credits are based on the number of class hours. As a general rule, students must attend more than two-thirds of the class hours in order to be eligible to take exams. Please make attending classes your number one priority.
Number of credits required for graduation
To graduate, students must be enrolled for at least four years and earn at least 124 credits. The breakdown of the minimum number of credits required to graduate varies depending on the department, course, and year of enrollment.
Robotics and Artificial Intelligence Course In today's rapidly changing society, social issues tend to become more diverse and complex. Responding to these issues requires more than just knowledge from a single or limited field of expertise; it requires multifaceted thinking that combines the humanities and sciences. For this reason, liberal arts education courses are divided into four fields: humanities, social science, natural science, and a field that combines the humanities and sciences. Please study each field in accordance with the graduation requirements to acquire a multifaceted perspective.
Subject classification
Number of units
Remarks
General Education
Liberal Arts Subjects
Humanities-related fields
2 or more
8 or more
Acquired 22 or more ※1
Social Sciences
Natural Sciences
2 or more
Interdisciplinary fields
－
First-year education subjects
2 or above (required)
Career-related courses
4 or above (required)
Information Education Subjects
2 or above (required)
Foreign Language Education
4 (Required)
Specialized courses
Compulsory
43
Total 90 or more
Optional compulsory
4※2、14※2
Elective
29
Free Choice
12
General Education and specialized subjects Excess and Courses taken in other departments
total
124
* Specialized subjects in other courses will be counted as specialized subjects minus elective subjects.
*1 Obtain 10 or more credits from five subject categories
*2Please refer to the course list for each course for details.
研究室
Students are studying a variety of research topics under the guidance of experienced faculty members.
