TIRT 視覺辨識無人車競賽
為了參與視覺辨識無人車競賽並挑戰不使用市售AI鏡頭而開發的土炮道路線辨識算法。
'%3e%3crect%20x='0'%20y='0'%20width='240'%20height='60'%20fill='%23FFD23F'%20fill-opacity='.8'/%3e%3crect%20x='0'%20y='0'%20width='240'%20height='60'%20fill='url(%23washi-yellow-p)'%20fill-opacity='1'/%3e%3crect%20x='0'%20y='0'%20width='240'%20height='60'%20fill='url(%23washi-yellow-sheen)'/%3e%3cpath%20d='M0%20.6H240'%20stroke='%23fff'%20stroke-opacity='.45'%20stroke-width='1.2'/%3e%3cpath%20d='M0%2059.4H240'%20stroke='%23F2B91A'%20stroke-opacity='.35'%20stroke-width='1.2'/%3e%3cpath%20d='M5.0%200.0%20L234.8%200%20L232.1%202.2%20L235.0%204.4%20L232.1%206.5%20L235.8%208.5%20L231.9%2010.5%20L237.0%2012.5%20L232.1%2014.3%20L234.6%2016.1%20L231.8%2017.8%20L237.5%2019.5%20L231.6%2022.1%20L234.9%2024.6%20L229.8%2026.8%20L236.6%2028.9%20L230.5%2030.7%20L235.2%2032.6%20L230.5%2034.3%20L234.5%2036.1%20L230.2%2038.3%20L235.3%2040.5%20L230.9%2043.0%20L235.3%2045.6%20L232.1%2047.6%20L235.0%2049.6%20L231.4%2051.2%20L236.8%2052.9%20L230.1%2054.8%20L235.6%2056.8%20L231.7%2059.4%20L236.6%2060.0%20L3.1%2060.0%20L9.8%2059.2%20L4.8%2057.4%20L7.6%2055.0%20L4.9%2052.5%20L8.5%2050.4%20L3.8%2048.3%20L10.3%2046.3%20L5.1%2044.2%20L8.0%2041.8%20L4.4%2039.4%20L7.8%2036.8%20L4.0%2034.3%20L7.6%2032.4%20L3.7%2030.4%20L9.7%2028.0%20L2.5%2025.5%20L8.2%2023.8%20L4.8%2022.2%20L7.7%2019.8%20L3.7%2017.4%20L7.5%2015.4%20L4.8%2013.5%20L9.0%2011.4%20L3.1%209.3%20L8.1%206.9%20L4.1%204.5%20L9.6%202.2Z'%20fill='none'%20stroke='%23fff'%20stroke-opacity='.35'%20stroke-width='1.6'/%3e%3c/g%3e%3c/svg%3e)
'%3e%3crect%20x='0'%20y='0'%20width='240'%20height='60'%20fill='%232EC4B6'%20fill-opacity='.8'/%3e%3crect%20x='0'%20y='0'%20width='240'%20height='60'%20fill='url(%23washi-mint-p)'%20fill-opacity='.75'/%3e%3crect%20x='0'%20y='0'%20width='240'%20height='60'%20fill='url(%23washi-mint-sheen)'/%3e%3cpath%20d='M0%20.6H240'%20stroke='%23fff'%20stroke-opacity='.45'%20stroke-width='1.2'/%3e%3cpath%20d='M0%2059.4H240'%20stroke='%231FA396'%20stroke-opacity='.35'%20stroke-width='1.2'/%3e%3cpath%20d='M4.8%200.0%20L236.2%200%20L231.2%202.2%20L235.1%204.4%20L230.1%206.8%20L236.5%209.2%20L232.0%2011.3%20L235.5%2013.4%20L231.8%2016.0%20L237.5%2018.6%20L232.4%2021.0%20L236.3%2023.5%20L231.4%2025.4%20L236.5%2027.2%20L231.1%2029.5%20L236.5%2031.8%20L232.1%2034.2%20L237.4%2036.5%20L229.6%2038.8%20L234.6%2041.0%20L232.5%2042.7%20L237.3%2044.4%20L231.6%2046.4%20L237.2%2048.4%20L231.6%2050.5%20L235.8%2052.7%20L232.3%2054.9%20L237.0%2057.0%20L232.0%2058.9%20L235.2%2060.0%20L4.8%2060.0%20L8.4%2060.0%20L3.6%2060.0%20L10.4%2057.9%20L4.8%2055.9%20L7.8%2054.2%20L2.9%2052.4%20L8.8%2049.9%20L3.1%2047.3%20L10.3%2045.4%20L3.4%2043.4%20L9.7%2040.9%20L4.1%2038.4%20L7.6%2035.9%20L4.6%2033.5%20L9.8%2031.3%20L5.3%2029.1%20L9.7%2026.8%20L3.9%2024.5%20L9.4%2022.1%20L5.0%2019.6%20L8.9%2017.4%20L3.0%2015.1%20L10.5%2013.1%20L4.8%2011.0%20L10.0%209.1%20L5.5%207.3%20L9.4%205.6%20L3.7%203.9%20L9.1%202.0Z'%20fill='none'%20stroke='%23fff'%20stroke-opacity='.35'%20stroke-width='1.6'/%3e%3c/g%3e%3c/svg%3e)
前言
在2022年暑假，我看到今年TIRT比賽的海報，其中視覺辨識無人車項目最讓我感興趣，因為視覺辨識是我沒接觸過的領域，我覺得可以趁機接觸這個領域，順便跳脫舒適圈一下。於是我馬上找了我們班上熱愛手作的同學組成了三人小隊，開始研發我們的自動駕駛小車車了。
視覺辨識設計想法
要能達成車子跟隨兩條白色跑道線所組成賽道，大部分人會使用市售的AI鏡頭模組來簡單的達成循線行走的目的，但由於我們時間還有3個月，我自認為不要做這種沒有技術含量的作法，於是我開始了自研跑道辨識系統的道路了。
不過由於我完全沒接觸過機器學習，所以我打算不用機器學習來挑戰製作一個跑道視覺辨識，下面會對我的視覺辨識做詳細的製作說明。
原理及效果
心得
本次比賽只提到這些部分，是因為雖然我們三個月前開始準備比賽，但是團隊合作效果並不理想，造成我個人專注在視覺辨識研發，以及過於相信車體研發的組員，導致我們在比賽前幾天，我的視覺辨識程式趨近於完成、只剩下調整參數階段，但車體研發組員卻尚未完成車體及硬體電路組裝。
所以我只能在比賽前一晚承擔了所有，開始寫arduino控制馬達程式、調整車體等等。但很不幸的，在比賽當天早上2點，我們的樹莓派無預警故障無法開機，經過30分鐘檢修後還是回天乏術，所以只能在群組上跟組員宣告比賽只能棄權的壞消息。
經過這次經驗，我學習到了時間分配的重要性，以及獲得身為隊長團隊領導能力的寶貴經驗，希望在往後的比賽能夠改進。
不過這次的視覺辨識研發也讓我學到了很多圖像處理的知識，其中我濾掉雜訊的方法是用侵蝕像素再膨脹的方法。本來以為我是用一個邪門的方法，但後來在github上看到也有人這樣用，瞬間有種想法跟大神一樣的優越感xd