【摘要】：在工業(yè)自動化和物流領(lǐng)域中,碼垛機器人是提高生產(chǎn)效率的重要設(shè)備,而運動軌跡規(guī)劃是機器人運動控制最核心的工作。本文以四自由度關(guān)節(jié)型碼垛機器人的軌跡規(guī)劃為研究課題,以時間最優(yōu)、脈動最優(yōu)、能耗最優(yōu)等多目標(biāo)最優(yōu)為規(guī)劃研究目標(biāo),重點進行了時間最優(yōu)關(guān)節(jié)柔順的軌跡二次規(guī)劃方法研究和基于碼垛工作環(huán)境因素的多目標(biāo)最優(yōu)規(guī)劃算法研究。首先,對四自由度關(guān)節(jié)型碼垛機器人進行運動學(xué)建模和分析。采用經(jīng)典的D-H方法對各關(guān)節(jié)及連桿進行運動學(xué)分析,建立了機器人正逆解模型,同時通過Adams進行了仿真驗證,為之后的軌跡規(guī)劃研究建立基礎(chǔ)。其次,進行時間最優(yōu)關(guān)節(jié)柔順的二次規(guī)劃方法研究。分析了傳統(tǒng)時間最優(yōu)規(guī)劃中存在的軸間等待問題,以時間最優(yōu)為前提,采用柔性非對稱S型曲線作為規(guī)劃的基礎(chǔ)曲線,結(jié)合采用線性插值法,進行關(guān)節(jié)加加速度柔和化,最終提出了一種適用的兩步規(guī)劃方法。再者,進行高適應(yīng)性的多目標(biāo)最優(yōu)軌跡規(guī)劃方法研究。增加考慮碼垛工作環(huán)境因素,以時間、脈動、能耗最優(yōu)等多目標(biāo)為研究對象,以B樣條曲線為基礎(chǔ)規(guī)劃曲線,采用模糊層次分析法對各目標(biāo)對象的權(quán)重進行劃分;通過NSGA-II算法求得多目標(biāo)最優(yōu)化問題的Pareto解集;并最終結(jié)合各目標(biāo)權(quán)重,通過近距離理想解法(TOPSIS)和灰色關(guān)聯(lián)度法相結(jié)合的改進TOPSIS法進行解集排序,并從中篩選出最優(yōu)軌跡。最后,進行實驗驗證。為了對以上兩種規(guī)劃方法進行實驗驗證,進行了碼垛機器人軟件系統(tǒng)的設(shè)計與實現(xiàn),并最終在碼垛機器人實驗平臺下,通過重復(fù)定位精度實驗和實際碼垛實驗,驗證了兩種規(guī)劃方法的正確性和有效性。研究結(jié)果表明,時間最優(yōu)關(guān)節(jié)柔順的二次規(guī)劃法能在不損失效率的情況下,最大限度地減少關(guān)節(jié)脈動;基于碼垛工作環(huán)境因素的多目標(biāo)規(guī)劃法,靈活性大,適用于碼垛工作環(huán)境多變和不同碼垛需求的場合,且改進TOPSIS法比未改進前更能選出最佳軌跡。以上兩種規(guī)劃方法對于碼垛機器人運動控制具有重要意義。
[Abstract]:In the field of industrial automation and logistics, palletizing robot is an important equipment to improve production efficiency, and motion trajectory planning is the core of robot motion control. In this paper, the trajectory planning of a four-degree-of-freedom joint palletizing robot is studied, and the multi-objective optimization, such as time optimization, pulsation optimization and energy consumption optimization, is taken as the research goal. This paper focuses on the research of the trajectory quadratic programming method of the time optimal joint compliance and the multi-objective optimal programming algorithm based on the palletizing working environment factor. Firstly, kinematics modeling and analysis of four-DOF joint palletizing robot are carried out. The classical D-H method is used to analyze the kinematics of joints and connecting rods, and the forward and inverse solution model of the robot is established. At the same time, the simulation by Adams is carried out to establish the foundation for the later trajectory planning research. Secondly, the quadratic programming method of time optimal joint compliance is studied. In this paper, the problem of inter-axis waiting in traditional time optimal programming is analyzed. Based on the premise of time optimization, flexible asymmetric S-shaped curve is used as the basic curve of programming, and linear interpolation method is used to soften the joint acceleration. Finally, a suitable two-step programming method is proposed. Furthermore, a multi-objective optimal trajectory planning method with high adaptability is studied. Considering the working environment factors of palletizing, taking time, pulsation and energy consumption as the research object, taking B-spline curve as the basic programming curve, using fuzzy analytic hierarchy process (FAHP) to divide the weight of each target object. The Pareto solution set of multi-objective optimization problem is obtained by NSGA-II algorithm. Finally, combined with the weight of each target, the improved TOPSIS method combined with the close distance ideal method (TOPSIS) and the grey correlation degree method was used to sort the set, and the optimal locus was screened out. Finally, experimental verification is carried out. In order to verify the above two planning methods, the software system of palletizing robot is designed and implemented. Finally, the experiment of positioning accuracy and actual palletizing is carried out on the platform of palletizing robot. The correctness and validity of the two programming methods are verified. The results show that the quadratic programming method of optimal time joint compliance can minimize the joint pulsation without loss of efficiency. The multi-objective programming method based on the working environment of palletizing is flexible and suitable for different palletizing environments and different palletizing requirements, and the improved TOPSIS method can select the best trajectory better than before. The above two planning methods are of great significance for the motion control of palletizing robots.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP242

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