本文選題：路徑規(guī)劃 + 移動機器人��； 參考：《北京交通大學》2017年碩士論文

【摘要】：路徑規(guī)劃是移動機器人完成任務過程中需要解決的主要問題之一。所謂路徑規(guī)劃是根據(jù)所處環(huán)境和運動約束條件生成一條或幾條從起始位置到終止位置之間的最優(yōu)路徑。對于大規(guī)模路徑規(guī)劃問題,需要快速生成多條符合要求的路徑，而傳統(tǒng)的全局路徑規(guī)劃算法執(zhí)行效率較低,不能夠滿足上述問題的要求。通過分析,我們發(fā)現(xiàn)移動機器人所處的不同場景間存在相似或者部分相似的情況,相似區(qū)域中移動機器人的運動方式和運動軌跡大致相同。這使得利用已有場景信息和路徑信息,優(yōu)化生成新路徑成為可能。本文圍繞相似場景下的路徑規(guī)劃問題展開研究，提出了一種基于典型路徑庫的移動機器人智能路徑規(guī)劃算法。該算法基于已有的場景和路徑信息,分析路徑的特征屬性形成知識,在給定的新場景中,利用路徑知識快速生成多條符合期望的路徑。算法由場景建模、場景相似性度量、相似路徑特征提取、路徑優(yōu)化生成、路徑評價等多個模塊組成。本文的主要工作包含以下幾個方面:(1)針對場景建模問題,本文研究了相似場景的特征屬性,采用聚類算法根據(jù)場景內(nèi)站位的聚集程度進行區(qū)域劃分,將場景劃分結(jié)果作為場景描述的主要依據(jù)。(2)針對場景相似性度量問題,本文將場景抽象為多邊形區(qū)域，，利用多邊形頂點匹配算法的思想,計算場景間的相似度,并使用動態(tài)規(guī)劃的方法求解出兩個場景間最大相似區(qū)域匹配序列。(3)針對典型路徑庫建立問題,本文提出“三段式”路徑構(gòu)建模型。本文從相似區(qū)域中提取相似路徑,通過局部與全局坐標映射關(guān)系,結(jié)合車式移動機器人的運動學特性,確定需求場景中的關(guān)鍵坐標點,從而建立典型路徑庫。(4)針對最優(yōu)路徑選擇問題,本文綜合考慮多種因素,提出路徑評價函數(shù)模型。通過實驗驗證,確定各個參數(shù)的權(quán)重比例,從而對典型路徑庫中的多條參考路徑進行評價排序。本文根據(jù)所提出的算法,搭建了場景布局和路徑規(guī)劃實驗平臺。通過大量仿真實驗,驗證了該算法的可行性。實驗結(jié)果表明本文提出的算法對于相似場景中大規(guī)模路徑規(guī)劃問題,能夠顯著提高效率,解決實際問題。
[Abstract]:Path planning is one of the main problems that need to be solved in the process of mobile robot task completion. The so-called path planning is to generate one or more optimal paths from the starting position to the terminating position according to the environment and motion constraints. For the large-scale path planning problem, it is necessary to quickly generate many paths that meet the requirements. However, the traditional global path planning algorithm is inefficient and can not meet the requirements of the above problems. Through analysis, we find that there are similar or partial similarities between different scenes of mobile robot, and the motion mode and trajectory of mobile robot in similar region are approximately the same. This makes it possible to optimize the generation of new paths using existing scenario information and path information. In this paper, an intelligent path planning algorithm for mobile robots based on typical path library is proposed. Based on the existing scene and path information, the algorithm analyzes the characteristic attributes of the path to form knowledge. In a given new scenario, the path knowledge is used to quickly generate multiple paths that meet the expectations. The algorithm consists of several modules, such as scene modeling, scene similarity measurement, similarity path feature extraction, path optimization generation, path evaluation and so on. The main work of this paper includes the following aspects: (1) aiming at the problem of scene modeling, this paper studies the characteristic attributes of similar scenes, and uses clustering algorithm to divide the regions according to the degree of aggregation of the stations in the scene. The result of scene partitioning is regarded as the main basis of scene description. (2) aiming at the problem of scene similarity measurement, this paper abstracts the scene into polygon region and calculates the similarity between scenes by using the idea of polygon vertex matching algorithm. Dynamic programming is used to solve the matching sequence of the two scenes. (3) aiming at the problem of establishing a typical path library, a "three-segment" path construction model is proposed in this paper. In this paper, the similarity path is extracted from the similar region, and the key coordinate points in the requirement scene are determined by mapping the local and global coordinates and combining the kinematics characteristics of the vehicular mobile robot. In order to establish a typical path library. (4) aiming at the problem of optimal path selection, this paper proposes a path evaluation function model considering a variety of factors. Through experimental verification, the weight ratio of each parameter is determined, and then the multiple reference paths in the typical path library are evaluated and sorted. According to the proposed algorithm, a scene layout and path planning experimental platform is built in this paper. The feasibility of the algorithm is verified by a large number of simulation experiments. Experimental results show that the proposed algorithm can significantly improve the efficiency and solve the practical problems for large-scale path planning problems in similar scenarios.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242

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