智能小车软件系统设计与路径规划方法研究

发布时间：2018-07-10 05:18

本文选题：模糊规则 + A*算法　；参考：《浙江理工大学》2017年硕士论文

【摘要】：轮式移动机器人是机器人学的一个重要分支,其在军事、太空、民用等各大领域都有着广阔的运用前景。路径规划问题是移动机器人研究领域中最关键的课题之一,它解决移动机器人在环境中如何行驶的问题。尽管当前对移动机器人路径规划以及软件系统的研究颇多,但随着社会经济的发展,相关研究仍难以满足各领域对机器人的专业性需求。因此,对机器人的路径规划及软件系统的研究依然具有非常高研究价值和现实意义。本文主要针对智能小车避障、路径规划以及软件系统的设计进行研究。首先,针对所研究的问题进行理论方面的论述,阐述了传统智能车框架技术以及当前的常见的路径规划方法。其次,提出了一种分层式的智能小车软件系统框架,通过将智能小车底层,控制层,服务器层分开,利用服务器强大的运算能力实现智能小车信息共享、协作、远程监控等功能。最后,对于智能小车的路径规划,我们采用基于A*算法的全局路径规划算法结合模糊避障算法作为智能小车的路径规划方法,解决了传统路径规划方法所存在的若干缺陷。本文工作的主要有以下三个贡献点:1)对研究国内外智能小车的现状进行分析总结,分析了传统智能小车软件框架的优缺点,对常见的路径规划方法进行分析与总结。2)提出一种基于模块功能的智能小车分层系统架构,解决了团队开发过程中存在的模块耦合以及开发交叉的问题,为智能小车软件系统的研究提供技术积累以及为团队开发管理提供思路借鉴。我们通过实验验证了该框架的实用性和有用性,此外该框架可以根据不同的需求在不同的层增加功能,扩展性较好。3)提出一种基于A*算法结合模糊避障方法的路径规划方法作为智能小车的路径规划方法。它解决了小车在路线规划好后,行驶过程中遇到障碍物的情形,使小车能够顺利沿着规划路劲行驶。
[Abstract]:Wheeled mobile robot is an important branch of robotics, which has a broad application prospect in military, space, civil and other fields. Path planning is one of the most important topics in the field of mobile robot research. It solves the problem of how the mobile robot travels in the environment. Although there are a lot of researches on path planning and software system of mobile robot, with the development of social economy, the related research is still difficult to meet the professional needs of robot in various fields. Therefore, the research on robot path planning and software system is still of great value and practical significance. This paper mainly focuses on the design of intelligent vehicle obstacle avoidance, path planning and software system. Firstly, the traditional intelligent vehicle frame technology and the current common path planning methods are discussed in this paper. Secondly, a layered intelligent car software system framework is proposed. By separating the bottom layer, control layer and server layer of the intelligent car, the information sharing and cooperation of the intelligent car can be realized by using the powerful computing power of the server. Remote monitoring and other functions. Finally, for the path planning of intelligent vehicle, we adopt the global path planning algorithm based on A* algorithm and fuzzy obstacle avoidance algorithm as the path planning method of intelligent vehicle, which solves some defects of the traditional path planning method. The main contributions of this paper are as follows: 1) analyzing and summarizing the current situation of domestic and foreign smart cars, and analyzing the advantages and disadvantages of the traditional smart car software framework. Based on the analysis and summary of common path planning methods, an intelligent vehicle layered system architecture based on module function is proposed, which solves the problems of module coupling and cross-development in the process of team development. It provides technology accumulation for the research of intelligent car software system and provides ideas for team development and management. We have verified the practicability and usefulness of the framework through experiments. In addition, the framework can add functions to different layers according to different requirements. (3) A path planning method based on A * algorithm and fuzzy obstacle avoidance method is proposed as a path planning method for intelligent vehicle. It solves the problem that the vehicle meets obstacles in the course of route planning, so that the car can run smoothly along the planned road.
【学位授予单位】：浙江理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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