Python × 電腦視覺 × 實體自駕車實作體驗
Python × Computer Vision × Hands-on Autonomous Vehicle Experience
隨著智慧車輛與電腦視覺技術的發展，自駕車的核心不只是機器學習模型，更包含即時影像辨識、環境理解與車輛控制整合能力。本次活動以做中學為核心，讓同學們執行Python程式，讀取自駕車攝影機畫面，進行影像判斷與車輛控制，讓同學們理解：
- 影像如何轉換為決策
- 決策如何轉換為車輛動作
- 感測、判斷與控制如何整合成完整系統
學生將透過實際操作自駕車，成功繞行道路一圈完成挑戰，體驗從影像處理到車輛控制的完整工程流程。
With the rapid development of intelligent vehicles and computer vision technologies, autonomous driving is not only about machine learning models, but also about the integration of real-time image perception, environmental understanding, and vehicle control. This hands-on workshop adopts a learning-by-doing approach. Participants will run Python programs to process camera images captured by an autonomous vehicle, perform visual decision-making, and control the vehicle’s movement. Through this experience, students will gain a practical understanding of:
- How visual data is transformed into driving decisions
- How decisions are converted into vehicle actions
- How sensing, decision-making, and control are integrated into a complete autonomous system
Participants will operate a real autonomous vehicle and complete a full lap on the track, experiencing the entire engineering workflow from image processing to vehicle control.
🎯活動目標 Workshop Objectives
- 建立學生對電腦視覺與智慧車輛控制系統的基礎理解
Build a fundamental understanding of computer vision and intelligent vehicle control systems
- 熟悉使用Python進行影像判斷與邏輯控制
Gain hands-on experience using Python for visual perception and logic-based control
- 培養感測－判斷－控制整合的系統思維
Develop system-level thinking by integrating sensing, decision-making, and control
- 透過分組挑戰培養問題解決能力與團隊合作能力
Strengthen problem-solving skills and teamwork through group-based challenges
- 做為後續進階AI、自主移動機器人與智慧車輛課程之入門體驗
Serve as an introductory experience for advanced courses in AI, autonomous robots, and intelligent vehicles
👥 活動對象與名額 Target Participants & Capacity
- 對象： 大學生（不限系所，但需具備 Python 基礎程式設計能力，若有機器學習/深度學習概念更佳）
Eligibility: Undergraduate students from all departments. Basic Python programming skills are required. Prior knowledge of machine learning or deep learning is a plus.
- 活動分組方式： 每隊3人，額滿8隊即截止。需自備筆電。
Team Format: Teams of 3 students. Maximum of 8 teams. Participants are required to bring their own laptops.
📍活動資訊 Event Information
- 活動時間：3/18 (三) 13:30 ~ 16:30
Date & Time： Wednesday, March 18, 13:30–16:30
- 地點：七館R70734教室
Venue：Room R70734, Building 7
- 講師：電機工程學系 林柏江老師
Instructor：Professor Lin, Po‑Chiang, Department of Electrical Engineering
報名網址：https://portalx.yzu.edu.tw/PortalSocialVB/FPage/PageActivityDetail.aspx?Menu=Act&ActID=16706
Registration Link：https://portalx.yzu.edu.tw/PortalSocialVB/FPage/PageActivityDetail.aspx?Menu=Act&ActID=16706
※完整參與活動者將提供服務學習時數3小時。
※ Students who complete the full workshop will receive 3 hours of Service Learning credit.
