DRT 496 · 3(2-3-5) · Year/term 4/2

Smart Robotics and Automation

หุ่นยนต์อัจฉริยะและระบบอัตโนมัติ

Progress

Notional hours: 150 h (online/self-study 75 · in class/lab 75)

Course description

Intelligent robots and modern automation; robot perception with cameras and LiDAR; kinematics, planning and control; applied ROS 2; integrating intelligent robots with UAS and industry.

Thai description

หุ่นยนต์อัจฉริยะและระบบอัตโนมัติสมัยใหม่ การรับรู้ของหุ่นยนต์ด้วยกล้องและ LiDAR จลนศาสตร์ การวางแผนและการควบคุม ระบบปฏิบัติการหุ่นยนต์ ROS 2 ขั้นประยุกต์ การบูรณาการหุ่นยนต์อัจฉริยะกับอากาศยานไร้คนขับและงานอุตสาหกรรม

Description source: New draft for the curriculum committee

Notes for the curriculum committee

ทับซ้อนกับ DRT 338 ควรกำหนดให้ DRT 496 เป็นวิชาต่อยอด

Course learning outcomes (CLO)

CLO	Outcome	PLO
CLO1	Explain intelligent robots and modern automation	PLO4
CLO2	Develop robots with perception and decision-making	PLO4
CLO3	Integrate intelligent robots with industry	PLO5

Learning modules

1Intelligent robots
Weeks 1–3 · 30 h2 KU

Online (before class) · 15 h

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

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

2Robot perception
Weeks 4–6 · 30 h2 KU

Online (before class) · 15 h

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

Computer vision and the path to edge AITH
LiDAR, radar and obstacle-avoidance sensorsIn development

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

3Planning and control
Weeks 7–9 · 30 h2 KU

Online (before class) · 15 h

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

Robot kinematics and motion planningIn development
Autonomous path planning and obstacle avoidanceIn development

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

4Applied ROS 2
Weeks 10–12 · 30 h1 KU

Online (before class) · 15 h

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

ROS 2 and flight-stack integrationIn development

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

5Industrial automation
Weeks 13–15 · 30 h1 KU

Online (before class) · 15 h

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

Industrial automation and PLCsIn development

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

Assessment (draft)

Labs and worksheets	35%
Module quizzes	10%
Midterm examination	20%
Mini-project or practical exam	35%

Knowledge domain

D02 Programming and digital technology D04 Sensors and embedded systems D06 Control, autopilot and navigation D07 Communications, networks and IoT D11 Artificial intelligence and computer vision D12 Automation, robotics and swarms

Key references

Lynch, K. M., & Park, F. C. (2017). Modern robotics: Mechanics, planning, and control. Cambridge University Press. link
Corke, P. (2023). Robotics, vision and control (3rd ed.). Springer.
Groover, M. P. (2019). Automation, production systems, and computer-integrated manufacturing (5th ed.). Pearson.