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    Please use this identifier to cite or link to this item: http://ccur.lib.ccu.edu.tw/handle/A095B0000Q/16

    Title: 工業自動化生產之碰撞偵測技術研發;Collision Detection of Industrial Automation
    Authors: 林家璿;LIN, CHIA-HSUAN
    Contributors: 資訊工程研究所
    Keywords: 碰撞偵測;Bounding Box;Oct-Tree Algorithms;GPU
    Date: 2018
    Issue Date: 2019-05-23 10:30:10 (UTC+8)
    Publisher: 資訊工程研究所
    Abstract: 自古以來,工業技術的進步一直是人類追求的目標,也是改善人類生活品質的關鍵之一。1760年工業革命開始,在這段時間裡,人類生產逐漸轉向新的製造過程,出現了以機器取代人力、獸力的趨勢,以大規模的工廠生產取代個體工場手工生產的一場生產與科技革命。由於機器的發明及運用成為了這個時代的標誌,因此歷史學家稱這個時代為機器時代(the Age of Machines)[1]。隨著科技的日新月異,現今人們追求工業技術進步的渴望並沒有改變。工廠內的生產線逐漸自動化,朝著機械完全取代人力的目標前進。因此,機械手臂在產線中的運動規劃以及安全指數尤為重要,本論文即針對機械手臂的碰撞偵測技術進行了改善,並且實作出模擬的產線。過去的碰撞偵測軟體或演算法多半利用Graphics Processing Unit(GPU)進行計算,物體的模擬是使用多邊形網格(Polygon mesh)進行繪製[2],此方法將需要很高的成本,並不符合工業需求。本論文改善此一缺點,利用Oct-Tree Algorithms分解物體造型[3],再使用Bounding Box技術將其形成包覆盒[4],藉此簡化計算量,在可接受的誤差範圍內,大幅降低計算時間。最後我們也在Rhino這個軟體上實作演算法,建構了一套工業上非常便利的產線模擬系統。
    Since ancient times, advances in industrial technology have been the goal pursued by mankind and one of the keys to improving the quality of human life. The Industrial Revolution began in 1760. During this time, human production gradually shifted to a new manufacturing process. There was a trend of replacing manpower and animal power with machines, and a production and technological revolution that replaced large-scale factory production with manual production in individual workshops. Since the invention and application of the machine became a symbol of this era, historians call this age the Age of Machines [1]. With the rapid development of science and technology, the desire of people to pursue industrial technological progress has not changed. The production line in the factory is gradually automated, moving towards the goal of fully replacing manpower by machinery. Therefore, the motion planning and safety index of the robot arm in the production line are particularly important. This paper has improved the collision detection technology for the robot arm and actually simulated the production line. In the past, collision detection software or algorithms were mostly calculated using the Graphics Processing Unit (GPU). Object simulation was performed using Polygon mesh [2]. This method will require high costs and does not meet the requirements. Industrial demand. This dissertation improves this shortcoming by using Oct-Tree Algorithms to decompose the object shape [3] and then use the Bounding Box technique to form a cover box [4]. This simplifies the calculation and reduces the error within an acceptable error range. calculating time. Finally, we also implemented the algorithm on the Rhino software to construct an industrially very convenient line simulation system.
    Appears in Collections:[資訊工程學系] 學位論文

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