王立昇Wang, Li-Sheng臺灣大學:應用力學研究所單幼玫Shan, Yu-MayYu-MayShan2010-05-182018-06-292010-05-182018-06-292009U0001-2707200901070300http://ntur.lib.ntu.edu.tw//handle/246246/183537本研究主旨為發展一戶外自動導航車系統。系統包含主控站、參考站和無人車三個部份。無人車整合了GPS接收機、電子羅盤、雙眼相機和六個超音波感測器等感測元件。無人車預先偵測前方障礙物形狀與位置，且在障礙物進入其運動方向之安全範圍時進行避障；藉由全球定位系統載波相位三次差分法（KGPS）進行全域定位，作為在無障礙物之狀況下之控制資訊；方位角則由電子羅盤輸出獲得，經由無線網路構成的各次系統資訊交換機制，使主控站得以監控無人車行為。 雙眼視覺處理方面，利用左右影像疊合時會產生一平面視差之原理得到無人車前方地理資訊。首先利用邊緣偵測取出左右影像輪廓，再使用影像處理方法將影像疊合找出並標出障礙物與地面的交界線。最後經由同點異像矩陣計算出前方障礙物的位置與距離，作為避障資訊之參考。 地形避障控制方面，引入位能場概念。由車體至終點及前方障礙物的距離分別計算引力及斥力；依障礙物邊緣座標點設計高斯分佈之能量場，計算總位能；其後使無人車行經於最小位能處所形成之平滑曲線，並控制其角度和速度輸出以規劃路徑。 即時避障控制方面，利用VHDL語言配合FPGA開發板設計一控制六顆超音波感測器輸出輸入電路，再透過超音波感測器得到距離資訊。此六個超音波感測器乃由設計控制器管理，經由規則庫系統推論無人車所需要的角度和速度輸出，對移動中的障礙物進行即時避障控制。 將上述感測器及其避障模式加以整合，使無人車在不同環境中能避障及抵達終點。觀察各個避障模式結果，驗證本論文的理論確實可行。The main theme of this thesis is to develop an outdoor navigation vehicle system. This system consists of three parts which are the main station, reference station, and an unmanned vehicle. The GPS receiver, electronic compass, stereo camera, and six ultrasonic sensors are integrated into the unmanned vehicle. The obstacle avoidance is performed by the vehicle which can detect the shape and position of the obstacles within a detectable range in the direction of its motion. The position of the unmanned vehicle is provided by GPS in an obstacle-free situation with the help of Triple Difference Carrier Phase method KGPS. The Heading angle is obtained through the output of an electronic compass. In addition, the main station can monitor the performance and behavior of the vehicle via the data exchange mechanism constructed by several sub-systems and the wireless network. With stereo vision, the geographic information ahead of the vehicle is obtained by the principle of plane induced parallax. The profiles of left and right vision are acquired by Canny Edge Detection algorithm. Then, an intersection line of the obstacle and the level ground is found by the way of image processing. Finally, the position and distance of the obstacle is calculated by the homography matrix method. The method of potential field is used to perform obstacles avoidance. The distance between the vehicle and the destination is used to compute the attractive force and those between the vehicle and obstacles are used to find the repulsive force. Gaussian distribution-like potential energy is derived for each obstacle. Then, the unmanned vehicle is required to move on a smooth curve with lowest potential energy by controlling its angular velocity and the motion velocity. For real time obstacle avoidance, the input and output circuits of the six ultrasonic sensors are designed by VHDL language and implemented by FPGA development kit. The information of distance is obtained through the ultrasonic sensors which are managed by the design controller. Finally, the real time moving obstacle avoidance is performed by the angle and velocity that are inferred from the rule-based system. Integrating the above-distributed schemes unmanned vehicle can avoid collisions with obstacles and arrive at the destination in different scenario. Experimental results show that the proposed navigation and control methodology are practicable.目錄謝 Ⅰ要 Ⅱbstract Ⅲ錄 Ⅴ目錄 Ⅷ目錄 XI一章 緒論 1.1 前言 1.2 研究動機與目的 1.3 文獻回顧與研究內容 2.4 論文架構 3二章 無人車系統架構 4.1 無人車硬體架構 5.2 無人車軟體架構 8三章 定位系統與感測器原理 9.1 GPS定位系統 9.1.1 載波相位三次差分定位法 9.2 雙眼視覺系統 13.2.1相機成像座標系統 13.2.2 對極幾何 15.2.3 基礎矩陣 16.2.4 平面同點異像 18.2.5 平面視差 22.2.6雙眼視覺障礙物偵測設計 24.3超音波測距系統 26.3.1 超音波的基本性質 27.3.2 超音波感測器的測距原理 27.3.3 超音波感測器的距離量測 28.3.4 超音波感測器的基本參數 29.3.5 超音波感測器的輸入和輸出控制 29四章 控制器設計與避障原理 31.1無人車運動方程 31.2位能場避障設計 33.2.1 位能場原理 33.2.2位能場模擬 34.3規則庫避障設計 36.3.1規則庫介紹 36.3.2超音波感測器的資訊整合 37.4避障控制器設計 40.4.目標追蹤控制設計 40.4.2 避障系統規劃 41.5無人車系統整合 42.5.1無人車導航系統架構 43.5.2 無人車導航系統與避障系統整合 44.5.3 處理時間分析 45五章 實驗結果與討論 47.1 無人車位能場避障實驗 49.1.1單一障礙物避障實驗A － 小型障礙物 49.1.2 單一障礙物避障實驗B － 大型障礙物 50.1.3多障礙物避障實驗A － 並排型障礙物 51.1.4多障礙物避障實驗B － 類隧道型障礙物 52.2 無人車即時避障實驗 53.2.1 規則庫測試結果 53.2.2 即時避障與位能場整合實驗 54.3 結果與討論 56六章 結論與未來工作 57考文獻 59application/pdf9225910 bytesapplication/pdfen-US雙眼相機立體視覺平面視差法位能場模型法導航避障控制Stereo cameraStereo visionPlane induced parallaxPotential field model methodNavigation obstacle controlthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/183537/1/ntu-98-R96543005-1.pdf