【摘要】：隨著人口老齡化壓力的日益加劇以及殘疾人口數(shù)目的不斷增多,提高老年人和殘疾人生活行動(dòng)的便攜性已成為急需解決的社會(huì)問(wèn)題,智能輪椅作為助老助殘產(chǎn)品中的重要分支受到國(guó)內(nèi)外研究者的廣泛關(guān)注。室內(nèi)建圖及自主導(dǎo)航作為智能輪椅的基礎(chǔ)功能,其中涉及的關(guān)鍵技術(shù)有SLAM(Simultaneous Localization And Mapping,即同時(shí)定位與建圖)、全局定位以及路徑規(guī)劃等。本文對(duì)智能輪椅室內(nèi)建圖及自主導(dǎo)航過(guò)程中涉及的關(guān)鍵技術(shù)進(jìn)行研究,主要工作如下:首先,研究了SLAM的數(shù)學(xué)模型,針對(duì)基于濾波的建圖算法無(wú)法在大環(huán)境中創(chuàng)建全局一致地圖的問(wèn)題,提出了一種基于圖優(yōu)化的建圖算法。該算法采用基于相關(guān)性的掃描匹配方法實(shí)現(xiàn)幀間匹配,利用局部地圖匹配完成回環(huán)檢測(cè),并使用位姿優(yōu)化消除累計(jì)誤差。通過(guò)仿真驗(yàn)證,該算法能夠在室內(nèi)大型環(huán)境中創(chuàng)建全局一致的地圖。其次,研究了基本蒙特卡洛定位算法,針對(duì)基本蒙特卡洛定位算法應(yīng)用于全局定位時(shí)存在的粒子收斂速度緩慢、樣本退化及粒子貧乏的問(wèn)題,提出了一種改進(jìn)的蒙特卡洛定位算法。該算法將擴(kuò)展卡爾曼濾波用于運(yùn)動(dòng)預(yù)測(cè)過(guò)程中的位姿估計(jì),同時(shí)將自適應(yīng)機(jī)制引入重采樣過(guò)程,自適應(yīng)地重采樣及調(diào)整粒子數(shù)。通過(guò)仿真驗(yàn)證,該算法提高了粒子的收斂速度以及定位的可靠性。再次,研究了A*算法,針對(duì)A*算法用于全局路徑規(guī)劃時(shí)存在的規(guī)劃效率低、規(guī)劃路徑轉(zhuǎn)折多的問(wèn)題,提出了一種雙向平滑A*算法,提高了全局路徑規(guī)劃的效率,得到了平滑的全局路徑。同時(shí)研究了DWA算法用于局部路徑規(guī)劃,并基于全局路徑規(guī)劃與局部路徑規(guī)劃相結(jié)合的思想,提出了一種基于改進(jìn)A*算法和DWA算法的混合路徑規(guī)劃方法。通過(guò)仿真驗(yàn)證,該方法能夠在已知環(huán)境中得到一條較優(yōu)且平滑的全局路徑,同時(shí)能夠在局部變化的環(huán)境中進(jìn)行避障。最后,搭建了智能輪椅實(shí)驗(yàn)平臺(tái),包括智能輪椅硬件平臺(tái)以及基于ROS的自主導(dǎo)航系統(tǒng)。在室內(nèi)復(fù)雜小環(huán)境和簡(jiǎn)單大環(huán)境中分別對(duì)智能輪椅平臺(tái)進(jìn)行了室內(nèi)環(huán)境建圖實(shí)驗(yàn)、定位及自主導(dǎo)航實(shí)驗(yàn),實(shí)驗(yàn)結(jié)果表明本文方法具有一定的效果,同時(shí)智能輪椅能夠在不同的室內(nèi)環(huán)境中實(shí)現(xiàn)建圖、定位及自主導(dǎo)航功能。
[Abstract]:With the increasing pressure of population ageing and the increasing number of people with disabilities, improving the portability of the lives of older persons and persons with disabilities has become a social problem that urgently needs to be addressed, As an important branch of assistive products, intelligent wheelchairs have attracted wide attention from researchers at home and abroad. Indoor mapping and autonomous navigation are the basic functions of intelligent wheelchair. The key technologies involved include slam (simultaneous localization And mapping), global positioning and path planning. The main work of this paper is as follows: firstly, the mathematical model of slam is studied. In order to solve the problem that the filter based map building algorithm can not create a global uniform map in a large environment, this paper proposes a graph building algorithm based on graph optimization. The algorithm uses correlation-based scanning matching to achieve inter-frame matching, uses local map matching to complete loop detection, and uses pose optimization to eliminate cumulative errors. Simulation results show that the algorithm can create a globally consistent map in a large indoor environment. Secondly, the basic Monte Carlo localization algorithm is studied. Aiming at the problems of the slow convergence of particles, the degradation of samples and the shortage of particles when the basic Monte Carlo localization algorithm is applied to global localization, An improved Monte Carlo localization algorithm is proposed. The extended Kalman filter is used to estimate the position and orientation of motion prediction, and the adaptive mechanism is introduced into the resampling process, which adaptively resamples and adjusts the number of particles. The simulation results show that the algorithm improves the convergence speed and the reliability of localization. Thirdly, the A * algorithm is studied. Aiming at the problems of low planning efficiency and many path turning points, a bidirectional smooth A * algorithm is proposed to improve the efficiency of global path planning. A smooth global path is obtained. At the same time, DWA algorithm is applied to local path planning. Based on the idea of combining global path planning with local path planning, a hybrid path planning method based on improved A * algorithm and DWA algorithm is proposed. The simulation results show that the proposed method can obtain an optimal and smooth global path in a known environment and can avoid obstacles in a locally changing environment. Finally, the experiment platform of intelligent wheelchair is built, including the hardware platform of intelligent wheelchair and the autonomous navigation system based on Ros. In the indoor complex environment and simple environment, the indoor environment mapping experiments, positioning and autonomous navigation experiments are carried out respectively. The experimental results show that this method has a certain effect. At the same time, intelligent wheelchair can build map, position and autonomous navigation in different indoor environment.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TH789;TP242

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