IGESSIGESS (Institute for Global Economics and Social Sciences)
MEC300XB(機械工学 / Mechanical engineering 300)Introduction to Intelligent RoboticsIntroduction to Intelligent Robotics
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 | IGESSIGESS (Institute for Global Economics and Social Sciences) |
添付ファイル名Attached documents | |
年度Year | 2024 |
授業コードClass code | H9700 |
旧授業コードPrevious Class code | |
旧科目名Previous Class title | |
開講時期Term | 春学期授業/Spring |
曜日・時限Day/Period | 木曜1時限木1/Thu.1 |
科目種別Class Type | |
キャンパスCampus | 小金井 |
教室名称Classroom name | 小西館‐W301 |
配当年次Grade | 3~4 |
単位数Credit(s) | 2 |
備考(履修条件等)Notes | |
他学部公開科目Open Program | |
他学部公開(履修条件等)Open Program (Notes) | |
グローバル・オープン科目Global Open Program | |
成績優秀者の他学部科目履修制度対象Interdepartmental class taking system for Academic Achievers | |
成績優秀者の他学部科目履修(履修条件等)Interdepartmental class taking system for Academic Achievers (Notes) | |
実務経験のある教員による授業科目Class taught by instructors with practical experience | |
SDGsCPSDGs CP | |
アーバンデザインCPUrban Design CP | |
ダイバーシティCPDiversity CP | |
未来教室CPLearning for the Future CP | |
カーボンニュートラルCPCarbon Neutral CP | |
千代田コンソ単位互換提供(他大学向け)Chiyoda Campus Consortium | |
カテゴリーCategory |
General Education Courses/総合教育科目 Global Open Program/グローバルオープン科目 |
科目主催学部Faculty Sponsored Department | 理工Science and Engineering |
すべて開くShow all
すべて閉じるHide All
授業の概要と目的(何を学ぶか)Outline and objectives
This course is an introduction to the theory of robotics. Therefore, it covers the fundamentals of the field, including homogeneous transformations, forward and inverse kinematics of robot manipulators, motion planning, trajectory generation and robot sensing. In the last three lectures, topics such as Genetic Algorithms, Neural Networks and Evolutionary Robotics will be explained.
到達目標Goal
The aim is to gain knowledge in the field of robot design, development and programming and also artificial intelligence and its application.
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 changes in the lesson plan will be presented in the learning support system.
Instructional methods include assigned readings, lectures, programming exercises and discussions. The feedback for assignments (tests and reports, etc.) are given during office hours.
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]:Introduction
A brief history, types of robots, some useful websites, textbooks and research journals.
2[対面/face to face]:Sensors and signal processing
Common robot sensors and their properties.
3[対面/face to face]:Image processing methods
Spatial domain transformations and edge detection.
4[対面/face to face]:Actuators
Different kinds of actuators, DC servo and brushless motors, model of a DC servo motor.
5[対面/face to face]:Manipulator kinematics
Homogeneous transformations and matrix methods, Euler angles; directional cosines; roll, pitch, yaw.
6[対面/face to face]:Manipulator kinematics
D-H parameters and link transforms.
Examples of kinematics of common robot manipulators.
7[対面/face to face]:Robot Inverse Kinematics
Study of Manipulator inverse kinematic solutions.
8[対面/face to face]:Velocity and statics of robot manipulators.
Jacobian matrix of robot manipulators.
9[対面/face to face]:Robot Dynamics
Lagrangian formulation for equations of motion of robot manipulators.
10[対面/face to face]:Modeling and analysis of wheeled mobile robots
Wheeled mobile robots and their Simulation using Matlab.
11[対面/face to face]:Control Theory
Feedback, feedforward and open loop control.
Linear first order lag processes.
Limitations of control theory.
12[対面/face to face]:Intelligent robot control
Reinforcement learning for control.
13[対面/face to face]:Intelligent robot control
Evolutionary approaches.
14[対面/face to face]:Intelligent robot control
Case studies and applications
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・復習等の授業時間外学習は、4時間を標準とする】Students are expected to download and read assigned readings prior to lectures. A number of problems will be solved during the lecture. The problems which will not be solved during the lecture, will be submitted as a report in t
テキスト(教科書)Textbooks
Handouts and other printed materials will be provided. They will be also made available for download.
参考書References
1. Schilling R J (1990). Fundamentals of Robotics - Analysis & Control.
2. Fu K, Gonzalez R and Lee C. Robotics (Control Sensing Vision & Intelligence).
成績評価の方法と基準Grading criteria
The assessment consists of two components: participation (20%), and the final report project (80%). Students, whose total points of evaluations of the exam and reports is 60 points or higher will pass.
学生の意見等からの気づきChanges following student comments
The course concentrates on creating links between theory and practice. Therefore, many real application examples will be considered.