室内移动机器人导航与定位系统设计与实现

发布时间：2018-09-19 14:21

【摘要】：在室内移动机器人研究领域中,导航与定位成为了主要的研究方向。大多数控制系统需要处理大量的数据,但是微处理器系统在处理、计算、分析数据的能力较弱。为了解决微处理器的缺点,通常把数据传输到PC机中,通过PC处理,完成对控制系统的数据处理。本文研究的室内移动机器人控制系统通过上位机、下位机两部分而设计。上位机通过具有强大数学运算能力的MATLAB软件为平台而搭建,具有强大的数据处理能力和人机交互控制界面。下位机主要是基于ARM芯片的STM 32作为控制平台,两者通过ZigBee无线通讯技术实现两者的通讯。这样设计能够节省了下位机的存储资源、提高了控制系统的运算能力、容易构建信息数据库等,提高机器人的灵敏度,加强了机器人的可控性。导航技术是移动机器人的核心。本文提出了一种PDSFA算法与dijkstra算法相结合,并基于自由空间法实现了室内移动机器人导航的路径规划关键问题。并与两种改进人工鱼群算法的结果对比,PDSFA算法具有运行时间短,稳定性好等优点。在已知的室内作业环境的情况下,还需要对作业环境进行建模。目前,建模的方法有很多,主要通过栅格法、可视图法、自由空间法、神经网络法等。本文提出了基于MATLAB图像处理工具箱获取室内环境的图像,并通过MATLAB获取图像中障碍物的坐标,完成了自由空间法中环境模型的构建,为室内移动机器人路径规划打下了基础。随着科学技术的发展,机器人定位技术的方法也随着发展。目前,GPS定位技术,军事、民用领域得到了广泛应用。然而,在民用领域中,受到各种因素的限制,在室内定位精度误差较大,所以未能在室内移动机器人中得到广泛应用。还有比较主流的定位方式中红外定位技术、超声波定位技术、视觉定位技术。本文主要采用RFID定位技术,基于每张RFID电子标签中都有唯一的ID号,机器人通过读取铺设在室内的ID卡,即可知道机器人的位置,实现机器人的定位功能。经过对各个模块和系统的测试,表明机器人在室内模拟家居环境下进行定位、导航、避障、上位机与下位机之间的通信,以及机器人通过自主决策完成路径规划,实现了基本功能,满足了系统设计的要求。通过以上的方法和实验,验证了本文提出的控制系统的可行性、有效性。但是,由于本文的研究和开发周期比较短,如RFID标签的面积过大,在定位技术方面存在一定的误差。因此,论文还需进一步的改进和加以研究。
[Abstract]:In the research field of indoor mobile robot, navigation and positioning have become the main research direction. Most control systems need to deal with a large amount of data, but microprocessor systems are weak in processing, computing, and analyzing data. In order to solve the shortcomings of the microprocessor, the data is usually transferred to the PC computer, and the data processing of the control system is completed through the PC processing. The indoor mobile robot control system studied in this paper is designed by two parts: upper computer and lower computer. The upper computer is built on the platform of MATLAB software which has powerful mathematical computing ability. It has powerful data processing ability and human-computer interactive control interface. The lower computer is mainly based on ARM chip STM 32 as the control platform, both through the ZigBee wireless communication technology to achieve the communication between the two. This design can save the storage resources of the lower computer, improve the computing ability of the control system, easily build the information database, improve the sensitivity of the robot and enhance the controllability of the robot. Navigation technology is the core of mobile robot. In this paper, a PDSFA algorithm combined with dijkstra algorithm is proposed, and the key problem of path planning for indoor mobile robot navigation is realized based on free space method. Compared with the results of two improved artificial fish swarm algorithms, the PDSFA algorithm has the advantages of short running time and good stability. In the case of known indoor working environment, it is also necessary to model the working environment. At present, there are many modeling methods, such as grid method, visual graph method, free space method, neural network method and so on. In this paper, the image of indoor environment is acquired based on MATLAB image processing toolbox, and the coordinates of obstacles in the image are obtained by MATLAB. The construction of environment model in free space method is completed, which lays the foundation for path planning of indoor mobile robot. With the development of science and technology, the method of robot positioning technology is also developing. At present, GPS positioning technology, military, civilian fields have been widely used. However, due to the limitation of various factors in the field of civil use, the accuracy of indoor positioning is large, so it can not be widely used in indoor mobile robots. There are more mainstream positioning methods infrared positioning technology, ultrasonic positioning technology, visual positioning technology. Based on the unique ID number in each RFID tag, the robot can know the position of the robot by reading the ID card laid in the room and realize the localization function of the robot. The tests of each module and system show that the robot can locate, navigate, avoid obstacles, communicate between the upper computer and the lower computer in the indoor simulated home environment, and the robot completes the path planning by independent decision. The basic function is realized and the requirement of system design is satisfied. The feasibility and effectiveness of the proposed control system are verified by the above methods and experiments. However, due to the short period of research and development in this paper, for example, the area of RFID tags is too large, there are some errors in positioning technology. Therefore, the paper needs further improvement and research.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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