UAT 314 · 3(3-0-6) · Year/term 1/1

Automation, Robotics and Intelligent Control Systems

ระบบอัตโนมัติ หุ่นยนต์ และการควบคุมอัจฉริยะ

Progress

Notional hours: 135 h (online/self-study 90 · in class/lab 45)

Course description

modeling of automation and robotic systems, kinematics and dynamics, modern control principles, state estimation, sensor fusion, motion planning, intelligent control, autonomous decision making, robotic system architectures, and integration of multiple platforms

Thai description

แบบจำลองระบบอัตโนมัติและหุ่นยนต์ จลนศาสตร์และพลวัต หลักการควบคุมสมัยใหม่ การประมาณสถานะ การรวมข้อมูลเซนเซอร์ การวางแผนการเคลื่อนที่ การควบคุมอัจฉริยะ การตัดสินใจอัตโนมัติ สถาปัตยกรรมระบบหุ่นยนต์ และการบูรณาการระบบหลายแพลตฟอร์ม

Description source: Curriculum draft (revised 28 Sep 2026)Previous site code: DRT 344

Course learning outcomes (CLO)

CLO	Outcome	PLO
CLO1	Explain automation, robotics and control	PLO1
CLO2	Analyse intelligent control for aircraft	PLO1PLO4
CLO3	Relate robotics to UAS applications	PLO5

Learning modules

1Automation
Weeks 1–3 · 27 hLesson 80 minquiz2 KU

Online (before class) · 18 h

Study the assigned knowledge units in advance, review media and take the module quiz

Industrial automation and PLCsIn development
Deep dive: MQTT and Eclipse Mosquitto for drone and IoT systemsTH

In class / field · 9 h

Lecture, case discussion and in-class problem solving

Learning evidence: Quiz results and submitted exercises

Open module + quiz

2Robotics and kinematics
Weeks 4–6 · 27 hLesson 90 minquiz1 KU

Online (before class) · 18 h

Study the assigned knowledge units in advance, review media and take the module quiz

Robot kinematics and motion planningIn development

In class / field · 9 h

Lecture, case discussion and in-class problem solving

Learning evidence: Quiz results and submitted exercises

Open module + quiz

3Feedback control
Weeks 7–9 · 27 hLesson 90 minquiz2 KU

Online (before class) · 18 h

Study the assigned knowledge units in advance, review media and take the module quiz

Feedback control and PID controllersIn development
Cascade control and flight-controller tuningIn development

In class / field · 9 h

Lecture, case discussion and in-class problem solving

Learning evidence: Quiz results and submitted exercises

Open module + quiz

4Intelligent control
Weeks 10–12 · 27 hLesson 90 minquiz3 KU

Online (before class) · 18 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 9 h

Lecture, case discussion and in-class problem solving

Learning evidence: Quiz results and submitted exercises

Open module + quiz

5Robots and drones
Weeks 13–15 · 27 hLesson 90 minquiz5 KU

Online (before class) · 18 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 9 h

Lecture, case discussion and in-class problem solving

Learning evidence: Quiz results and submitted exercises

Open module + quiz

Assessment (draft)

Quizzes and exercises	20%
Midterm examination	30%
Final examination	40%
Participation and discussion	10%

Knowledge domain

D02 Programming and digital technology D04 Sensors and embedded systems D06 Control, autopilot and navigation D07 Communications, networks and IoT D08 Mission planning, flight and simulation D11 Artificial intelligence and computer vision D12 Automation, robotics and swarms D13 Surveying, mapping and geoinformatics

Key references

Lynch, K. M., & Park, F. C. (2017). Modern robotics: Mechanics, planning, and control. Cambridge University Press. link
Åström, K. J., & Murray, R. M. (2021). Feedback systems: An introduction for scientists and engineers (2nd ed.). Princeton University Press. link
Groover, M. P. (2018). Automation, production systems, and computer-integrated manufacturing (5th ed.). Pearson. link