【摘要】：多移動(dòng)機(jī)器人系統(tǒng)是隨著現(xiàn)代社會(huì)的發(fā)展而興起的一項(xiàng)新興機(jī)器人研究方向,它能夠完成單個(gè)機(jī)器人無(wú)法完成的任務(wù)。路徑規(guī)劃是多移動(dòng)機(jī)器人完成任務(wù)的前提。本文從研究單個(gè)移動(dòng)機(jī)器人的路徑規(guī)劃到多移動(dòng)機(jī)器人的編隊(duì)控制以及一致性運(yùn)動(dòng)等進(jìn)行了深入的研究。針對(duì)移動(dòng)機(jī)器人路徑規(guī)劃和多移動(dòng)機(jī)器人編隊(duì)控制這兩項(xiàng)內(nèi)容,分別建立相應(yīng)模型,提出相應(yīng)優(yōu)化算法,并對(duì)所提算法進(jìn)行仿真驗(yàn)證,分析實(shí)驗(yàn)結(jié)果。移動(dòng)機(jī)器人路徑規(guī)劃部分,對(duì)比了傳統(tǒng)路徑規(guī)劃算法,分析了現(xiàn)有路徑規(guī)劃算法的優(yōu)缺點(diǎn)。針對(duì)傳統(tǒng)人工勢(shì)場(chǎng)法對(duì)機(jī)器人路徑規(guī)劃的缺點(diǎn),提出了一種結(jié)合機(jī)器人位置、速度、加速度及障礙物位置等信息的改進(jìn)人工勢(shì)場(chǎng)法,并且給出了幾種解決局部最小的方法,改進(jìn)人工勢(shì)場(chǎng)法能夠有效完成單移動(dòng)機(jī)器人的路徑規(guī)劃,但路徑規(guī)劃用時(shí)較長(zhǎng),路徑不夠平滑;針對(duì)人工勢(shì)場(chǎng)法自身的缺陷,改進(jìn)一種多層Morphin搜索樹算法,提出一種將改進(jìn)人工勢(shì)場(chǎng)法和多層Morphin搜索樹算法相結(jié)合的混合算法,在人工勢(shì)場(chǎng)法進(jìn)行路徑規(guī)劃的同時(shí),利用多層Morphin搜索樹對(duì)附近障礙物進(jìn)行搜索,保證整個(gè)機(jī)器人路徑規(guī)劃過(guò)程中路徑的平滑性和完成路徑規(guī)劃的效率。仿真實(shí)驗(yàn)表明該算法的有效性。多移動(dòng)機(jī)器人系統(tǒng)編隊(duì)控制部分,分析傳統(tǒng)多移動(dòng)機(jī)器人的編隊(duì)控制算法,比較其優(yōu)缺點(diǎn)。分析多移動(dòng)機(jī)器人系統(tǒng)的運(yùn)動(dòng)控制模型,并建立改進(jìn)的多機(jī)器人編隊(duì)中的機(jī)器人之間的勢(shì)場(chǎng)函數(shù)、機(jī)器人與障礙物之間的勢(shì)場(chǎng)函數(shù);基于多移動(dòng)機(jī)器人系統(tǒng)的運(yùn)動(dòng)控制模型以及改進(jìn)的多機(jī)器人編隊(duì)中兩種勢(shì)場(chǎng)函數(shù),對(duì)機(jī)器人的編隊(duì)形成進(jìn)行了分析,改進(jìn)的基于人工勢(shì)場(chǎng)法的隊(duì)形控制能夠有效完成編隊(duì),但只能形成一種固定隊(duì)形,不能隨意變換隊(duì)形。針對(duì)基于人工勢(shì)場(chǎng)法的隊(duì)形控制的缺點(diǎn),引入虛擬領(lǐng)航者的概念,提出基于人工勢(shì)場(chǎng)和虛擬領(lǐng)航者的多移動(dòng)機(jī)器人系統(tǒng)控制,用數(shù)學(xué)方法證明所提算法的穩(wěn)定性。仿真實(shí)驗(yàn)表明提出的基于人工勢(shì)場(chǎng)和虛擬領(lǐng)航者的方法在隊(duì)形形成、隊(duì)形變換及多移動(dòng)機(jī)器人避障環(huán)節(jié)都能夠有效快速完成。
[Abstract]:With the development of modern society, multi-mobile robot system is an emerging research direction of robot. It can accomplish tasks that can not be accomplished by a single robot. Path planning is a prerequisite for multiple mobile robots to complete their tasks. In this paper, the path planning of a single mobile robot, the formation control of a multi-mobile robot and the consistent motion of a mobile robot are studied in depth. Aiming at the two aspects of mobile robot path planning and multi-mobile robot formation control, the corresponding models are established, the corresponding optimization algorithm is proposed, and the proposed algorithm is verified by simulation and the experimental results are analyzed. In the part of path planning of mobile robot, the traditional path planning algorithm is compared, and the advantages and disadvantages of the existing path planning algorithm are analyzed. Aiming at the disadvantage of traditional artificial potential field method for robot path planning, an improved artificial potential field method combining robot position, velocity, acceleration and obstacle position is proposed, and several methods to solve local minimum are given. The improved artificial potential field method can effectively complete the path planning of a single mobile robot, but the path planning takes a long time and the path is not smooth enough. In view of the defects of the artificial potential field method, a multi-layer Morphin search tree algorithm is improved, and a hybrid algorithm which combines the improved artificial potential field method and the multi-layer Morphin search tree algorithm is proposed. The artificial potential field method is used for path planning at the same time. The multi-layer Morphin search tree is used to search the nearby obstacles to ensure the smoothness of the path and the efficiency of the path planning in the whole robot path planning process. Simulation results show that the algorithm is effective. In the part of formation control of multi-mobile robot system, the formation control algorithm of traditional multi-mobile robot is analyzed, and its advantages and disadvantages are compared. The motion control model of the multi-mobile robot system is analyzed and the potential field function between the robots in the improved multi-robot formation and the potential field function between the robot and the obstacle is established. Based on the motion control model of multi-mobile robot system and the two potential field functions of the improved multi-robot formation, the formation of the robot is analyzed. The improved formation control based on the artificial potential field method can effectively complete the formation. But can only form one kind of fixed formation, cannot change the formation at will. Aiming at the disadvantage of formation control based on artificial potential field method, the concept of virtual navigator is introduced, and the multi-mobile robot system control based on artificial potential field and virtual navigator is proposed. The stability of the proposed algorithm is proved by mathematical method. The simulation results show that the proposed method based on artificial potential field and virtual navigator can be completed efficiently and quickly in formation transformation and obstacle avoidance of multi-mobile robot.
【學(xué)位授予單位】：安徽工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP242

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