DRT 493 · 3(2-3-5) · Year/term 4/2

Autonomous Navigation Technology

เทคโนโลยีการนำร่องอัตโนมัติ

Progress

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

Course description

Autonomous navigation architecture; state estimation and sensor fusion; path planning and obstacle avoidance; ROS 2 for navigation; testing in simulators and assessing navigation reliability.

Thai description

สถาปัตยกรรมการนำร่องอัตโนมัติ การประมาณสถานะและการหลอมรวมข้อมูลเซนเซอร์ การวางแผนเส้นทางและการหลบหลีกสิ่งกีดขวาง ระบบปฏิบัติการหุ่นยนต์ ROS 2 กับการนำร่อง การทดสอบในเครื่องจำลองและการประเมินความน่าเชื่อถือของระบบนำร่อง

Description source: New draft for the curriculum committee

Course learning outcomes (CLO)

CLO	Outcome	PLO
CLO1	Explain autonomous navigation architecture	PLO1PLO4
CLO2	Develop path planning and obstacle avoidance	PLO4
CLO3	Test navigation systems in simulation	PLO3PLO4

Learning modules

1Autonomous navigation
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

2Sensor fusion
Weeks 4–6 · 30 h1 KU

Online (before class) · 15 h

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

State estimation with Kalman filters/EKFIn 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

3Path planning
Weeks 7–9 · 30 h1 KU

Online (before class) · 15 h

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

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

4ROS 2 for navigation
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

5Testing in simulators
Weeks 13–15 · 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

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 D08 Mission planning, flight and simulation D12 Automation, robotics and swarms

Key references

Siegwart, R., Nourbakhsh, I. R., & Scaramuzza, D. (2011). Introduction to autonomous mobile robots (2nd ed.). MIT Press.
Thrun, S., Burgard, W., & Fox, D. (2005). Probabilistic robotics. MIT Press.
Open Robotics. ROS 2 documentation. link