理工学研究科Graduate School of Science and Engineering
MEC700X1（機械工学 / Mechanical engineering 700）ヒューマンロボティクス特別研究１Ａ・１Ｂ・２Ａ・２Ｂ・３Ａ・３Ｂ Advanced Human Robotics 1A･1B･2A･2B･3A･3B
チャピ ゲンツィCAPI Genci
授業コードなどClass code etc
| 学部・研究科Faculty/Graduate school | 理工学研究科Graduate School of Science and Engineering |
| 添付ファイル名Attached documents | |
| 年度Year | 2024 |
| 授業コードClass code | YA424 |
| 旧授業コードPrevious Class code | |
| 旧科目名Previous Class title | |
| 開講時期Term | 春学期・秋学期/Spring・Fall |
| 曜日・時限Day/Period | 集中・その他/intensive・other courses |
| 科目種別Class Type | |
| キャンパスCampus | 小金井 / Koganei |
| 教室名称Classroom name | |
| 配当年次Grade | |
| 単位数Credit(s) | |
| 備考（履修条件等）Notes | |
| 実務経験のある教員による授業科目Class taught by instructors with practical experience | |
| カテゴリーCategory | 機械工学専攻 |
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Outline (in English)
To provide students with comprehensive knowledge on human robotics systems and improve research and presentation skills.
授業で使用する言語Default language used in class
英語 / English
授業の概要と目的（何を学ぶか）Outline and objectives
The course is primarily for graduate students with a strong motivation and a keen interest in research. The course will provide students with a comprehensive introduction to the area of intelligent robots and their applications in human environments. In addition to the weekly readings, presentations, and discussions, students will be involved in research project involving hardware, software and performance evaluation of developed robotic systems.
到達目標Goal
Students will be introduced to the area of intelligent robots and their applications in human environment. Students will acquire a deep knowledge on robot hardware, intelligent algorithms such Neural networks, Genetic Algorithms and Deep Learning. In addition, students will develop problem solving and critical thinking ability.
この授業を履修することで学部等のディプロマポリシーに示されたどの能力を習得することができるか（該当授業科目と学位授与方針に明示された学習成果との関連）Which item of the diploma policy will be obtained by taking this class?
ディプロマポリシーのうち、「DP1」「DP2」「DP3」「DP4」「DP5」に関連
授業で使用する言語Default language used in class
英語 / English
授業の進め方と方法Method(s)（学期の途中で変更になる場合には、別途提示します。 /If the Method(s) is changed, we will announce the details of any changes. ）
The students will master their knowledge in Human robotics by long term projects, survey of scientific literature, survey of specialized books and presentation of their findings.
アクティブラーニング（グループディスカッション、ディベート等）の実施Active learning in class (Group discussion, Debate.etc.)
あり / Yes
フィールドワーク（学外での実習等）の実施Fieldwork in class
なし / No
授業計画Schedule
授業形態/methods of teaching：対面/face to face
※各回の授業形態は予定です。教員の指示に従ってください。
1[対面/face to face]：Guidance
Explanation of the lecture content
2[対面/face to face]：Literature review
Survey and discussion on previous research.
3[対面/face to face]：Literature review
Survey and discussion on previous research.
4[対面/face to face]：Literature review
Survey and discussion on previous research.
5[対面/face to face]：Neural Networks
Several neural networks architectures will be explained
6[対面/face to face]：Neural Networks
Several neural networks architectures will be explained
7[対面/face to face]：Neural Networks
Several neural networks architectures will be explained
8[対面/face to face]：Deep Learning
Deep learning theory will be introduced
9[対面/face to face]：Deep Learning
Deep learning theory will be introduced
10[対面/face to face]：Deep Learning
Deep learning theory will be introduced
11[対面/face to face]：Genetic algorithm
Theory of Genetic Algorithm will be explained
12[対面/face to face]：Genetic algorithm
Theory of Genetic Algorithm will be explained
13[対面/face to face]：Genetic algorithm
Theory of Genetic Algorithm will be explained
14[対面/face to face]：Robot vision
Object recognition, masking and Deep learning for object recognition will be discussed
15[対面/face to face]：Robot vision
Object recognition, masking and Deep learning for object recognition will be discussed
16[対面/face to face]：Robot vision
Object recognition, masking and Deep learning for object recognition will be discussed
17[対面/face to face]：Robot Software
Robot programming and robot operating system will be explained
18[対面/face to face]：Robot Software
Robot programming and robot operating system will be explained
19[対面/face to face]：Robot Software
Robot programming and robot operating system will be explained
20[対面/face to face]：Robot Software
Robot programming and robot operating system will be explained
21[対面/face to face]：Robot Hardware
Robot sensor and actuators will be explained
22[対面/face to face]：Robot Hardware
Robot sensor and actuators will be explained
23[対面/face to face]：Robot Hardware
Robot sensor and actuators will be explained
24[対面/face to face]：Intelligent robot navigation
Goal oriented, obstacle avoidance, SLAM techniques will be discussed
25[対面/face to face]：Intelligent robot navigation
Goal oriented, obstacle avoidance, SLAM techniques will be discussed
26[対面/face to face]：Intelligent robot navigation
Goal oriented, obstacle avoidance, SLAM techniques will be discussed
27[対面/face to face]：System integration
Integrating software and hardware elements for robot development
28[対面/face to face]：System integration
Integrating software and hardware elements for robot development
授業時間外の学習（準備学習・復習・宿題等）Work to be done outside of class (preparation, etc.)
【本授業の準備・復習時間は、各3時間を標準とします。】Students has to read the materials suggested. Work individually in the selected project.
テキスト（教科書）Textbooks
A list of reference books and articles will be given through the lectures.
参考書References
Robotics, Vision and Control
Fundamental Algorithms in MATLAB,
Peter Corke, 2017
成績評価の方法と基準Grading criteria
Grading will be based mainly on the final project, in-class presentation, attendance and participation.
学生の意見等からの気づきChanges following student comments
Questionnaires are not considered