本文選題：地圖創(chuàng)建　切入點(diǎn)：ROS　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：近年來(lái),移動(dòng)機(jī)器人在各方面的應(yīng)用日益廣泛,與之相關(guān)的技術(shù)已在國(guó)內(nèi)外機(jī)器人領(lǐng)域掀起研究熱潮。對(duì)環(huán)境的認(rèn)識(shí)和定位從而實(shí)現(xiàn)自主導(dǎo)航是移動(dòng)機(jī)器人智能化的重要標(biāo)志和特征。未知環(huán)境下的即時(shí)定位與地圖構(gòu)建(SLAM)一直是移動(dòng)機(jī)器人技術(shù)領(lǐng)域的研究熱點(diǎn)。本項(xiàng)目面向室內(nèi)服務(wù)機(jī)器人系統(tǒng),開(kāi)展基于ROS的移動(dòng)機(jī)器人建圖導(dǎo)航相關(guān)技術(shù)研究,具體包括基于ROS的移動(dòng)機(jī)器人操作系統(tǒng)開(kāi)發(fā)、室內(nèi)環(huán)境自主探索建圖、以及局部路徑規(guī)劃等方面,具體研究?jī)?nèi)容如下。首先,設(shè)計(jì)了移動(dòng)機(jī)器人的硬件結(jié)構(gòu),完成機(jī)器人的傳感器等硬件系統(tǒng)搭建。在軟件控制系統(tǒng)方面,基于模塊化、分布式計(jì)算的設(shè)計(jì)思想,開(kāi)發(fā)了基于ROS的移動(dòng)機(jī)器人系統(tǒng)平臺(tái),對(duì)移動(dòng)機(jī)器人的傳感器信息采集、移動(dòng)控制、建圖導(dǎo)航及環(huán)境觀測(cè)等節(jié)點(diǎn)進(jìn)行了設(shè)計(jì),最終搭建了一套完整的建圖導(dǎo)航機(jī)器人系統(tǒng)。該機(jī)器人能夠進(jìn)行實(shí)時(shí)的地圖創(chuàng)建與導(dǎo)航,同時(shí)具備較好的人機(jī)交互能力。其次,針對(duì)目前SLAM系統(tǒng)中狀態(tài)估計(jì)無(wú)跡卡爾曼濾波算法(UKF)計(jì)算量大的問(wèn)題,提出了基于局部采樣的UKF狀態(tài)估計(jì)算法。根據(jù)算法中狀態(tài)向量的特性,在UKF算法的UT采樣過(guò)程中采用僅對(duì)部分與當(dāng)前狀態(tài)估計(jì)相關(guān)數(shù)據(jù)進(jìn)行采樣的策略,降低了狀態(tài)估計(jì)的計(jì)算復(fù)雜度。對(duì)新的采樣算法進(jìn)行公式推導(dǎo)分析,并通過(guò)仿真分析,驗(yàn)證了提出的算法在保證濾波定位精度的同時(shí)降低計(jì)算量,提高機(jī)器人建圖的實(shí)時(shí)性。提出了基于全局路徑的改進(jìn)動(dòng)態(tài)窗口(DWA)局部路徑規(guī)劃算法。首先通過(guò)對(duì)傳統(tǒng)的DWA算法進(jìn)行公式分析及仿真實(shí)驗(yàn)研究,針對(duì)其評(píng)價(jià)函數(shù)中存在非必需項(xiàng)和特殊環(huán)境導(dǎo)航效果差的問(wèn)題,提出了基于全局路徑規(guī)劃的DWA算法,并通過(guò)MATLAB實(shí)驗(yàn)仿真分析證明改進(jìn)方法的有效性與魯棒性。最后,利用搭建的移動(dòng)機(jī)器人實(shí)驗(yàn)平臺(tái)對(duì)機(jī)器人的自主探索SLAM進(jìn)行了實(shí)驗(yàn),驗(yàn)證了基于局部采樣的UKF定位算法和改進(jìn)的DWA局部路徑規(guī)劃的算法的可行性。
[Abstract]:In recent years, mobile robots have been widely used in various fields. The related technologies have aroused a research boom in the field of robotics at home and abroad. Understanding and locating the environment to realize autonomous navigation is an important sign and feature of the intelligent mobile robot. Map building (slam) has always been a hot topic in the field of mobile robot technology. Research on mobile robot mapping and navigation technology based on ROS is carried out, including the development of mobile robot operating system based on ROS, autonomous exploration and mapping of indoor environment, and local path planning and so on. The specific research contents are as follows. The hardware structure of the mobile robot is designed, and the hardware system such as the sensor of the robot is built. In the aspect of software control system, the platform of mobile robot system based on ROS is developed based on the design idea of modularization and distributed computing. The sensor information collection, mobile control, map building and navigation and environment observation of mobile robot are designed. Finally, a complete mapping navigation robot system is built. The robot can create and navigate maps in real time. At the same time, it has good human-computer interaction ability. Secondly, aiming at the problem that the state estimation unscented Kalman filter algorithm in SLAM system is computationally large, A state estimation algorithm for UKF based on local sampling is proposed. According to the characteristics of the state vector in the algorithm, only part of the data related to the current state estimation is sampled in the UT sampling process of the UKF algorithm. The computational complexity of state estimation is reduced. The formula derivation and analysis of the new sampling algorithm are carried out, and the simulation results show that the proposed algorithm not only ensures the accuracy of filtering location, but also reduces the computational complexity. An improved dynamic window DWA-based local path planning algorithm based on global path is proposed to improve the real-time performance of robot mapping. Firstly, the traditional DWA algorithm is studied by formula analysis and simulation experiments. In order to solve the problem of non-essential item and poor navigation effect in special environment, the DWA algorithm based on global path planning is proposed, and the effectiveness and robustness of the improved method are proved by MATLAB simulation. Based on the experimental platform of mobile robot, the autonomous exploration SLAM of the robot is tested, and the feasibility of the UKF location algorithm based on local sampling and the improved DWA local path planning algorithm is verified.
【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)】：TP242
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本文編號(hào)：1658333