IGESS (Institute for Global Economics and Social Sciences)

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MEC300XB(機械工学 / Mechanical engineering 300)
Introduction to Intelligent Robotics

CAPI Genci

Class code etc
Faculty/Graduate school IGESS (Institute for Global Economics and Social Sciences)
Attached documents
Year 2022
Class code H9700
Previous Class code
Previous Class title
Term 春学期授業/Spring
Day/Period 木1/Thu.1
Class Type
Campus 小金井
Classroom name 各学部・研究科等の時間割等で確認
Grade 3~4
Credit(s) 2
Notes
Open Program
Open Program (Notes)
Global Open Program
Interdepartmental class taking system for Academic Achievers
Interdepartmental class taking system for Academic Achievers (Notes)
Class taught by instructors with practical experience
SDGs CP
Urban Design CP
Diversity CP
Learning for the Future CP
Carbon Neutral CP
Chiyoda Campus Consortium
Category General Education Courses/総合教育科目
Global Open Program/グローバルオープン科目
Faculty Sponsored Department Science and Engineering

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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.

Goal

The aim is to gain knowledge in the field of robot design, development and programming and also artificial intelligence and its application.

Default language used in class

英語 / English

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.

Active learning in class (Group discussion, Debate.etc.)

あり / Yes

Fieldwork in class

なし / No

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[未定/undecided]:Introduction

A brief history, types of robots, some useful websites, textbooks and research journals.

2[未定/undecided]:Sensors and signal processing

Common robot sensors and their properties.

3[未定/undecided]:Image processing methods

Spatial domain transformations and edge detection.

4[未定/undecided]:Actuators

Different kinds of actuators, DC servo and brushless motors, model of a DC servo motor.

5[未定/undecided]:Manipulator kinematics

Homogeneous transformations and matrix methods, Euler angles; directional cosines; roll, pitch, yaw.

6[未定/undecided]:Manipulator kinematics

D-H parameters and link transforms.
Examples of kinematics of common robot manipulators.

7[未定/undecided]:Robot Inverse Kinematics

Study of Manipulator inverse kinematic solutions.

8[未定/undecided]:Velocity and statics of robot manipulators.

Jacobian matrix of robot manipulators.

9[未定/undecided]:Robot Dynamics

Lagrangian formulation for equations of motion of robot manipulators.

10[未定/undecided]:Modeling and analysis of wheeled mobile robots

Wheeled mobile robots and their Simulation using Matlab.

11[未定/undecided]:Control Theory

Feedback, feedforward and open loop control.
Linear first order lag processes.
Limitations of control theory.

12[未定/undecided]:Intelligent robot control

Reinforcement learning for control.

13[未定/undecided]:Intelligent robot control

Evolutionary approaches.

14[未定/undecided]:Intelligent robot control

Case studies and applications

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

Textbooks

Handouts and other printed materials will be provided. They will be also made available for download.

References

1. Schilling R J (1990). Fundamentals of Robotics - Analysis & Control.
2. Fu K, Gonzalez R and Lee C. Robotics (Control Sensing Vision & Intelligence).

Grading criteria

The assessment consists of two components: reports and the final project. Students, whose total points of evaluations of the exam and reports is 60 points or higher will pass.

Changes following student comments

The course concentrates on creating links between theory and practice. Therefore, many real application examples will be considered.