摘要
自主式移动机器人具有高度自规划、自组织和自适应能力,适合于在复杂的非结构化环境中工作。其目标是在没有人的干预、无需对环境做任何规定和改变的条件下有目的地移动和完成相应任务。所以,在自主式移动机器人相关技术中,导航是其中一个重要组成部分,也是移动机器人实现智能化以至完全自主的关键技术。我国在智能移动机器人研究方面虽然已经取得了一定的成果,但由于起步较晚,在研究和应用方面都落后于一些西方国家,而且还没有达到完全实用。因此,进行这项研究,具有一定的理论意义和工程应用意义。
移动机器人导航系统主要内容包括移动机器人的定位和路径规划。为了赋予机器人智能和自主的能力,本文对移动机器人导航系统进行了分析研究。
首先介绍了移动机器人的发展状况,分析了国内外移动机器人研究现状。并综合分析比较了目前常用的移动机器人定位和路径规划技术,结合设计需求,提出了室外自主移动机器人定位及路径规划比较合理的总体设计方案。
然后根据实验需要编写移动机器人控制程序,以便于方便地应用导航算法。在控制软件的编写过程中,充分考虑了机器人硬件平台可变的因素,创新性的将设计模式引入,使程序可以很好地应对变化,并且尽量使用了跨平台技术,为将来的平台移植做好了准备。
针对定位本文分析研究了GPS定位,DR导航原理。GPS定位存在误差大,有盲区等缺点;而DR航位推算存在初始准确但误差随时间累积的问题。因此,对移动机器人运动进行建模并使用卡尔曼滤波将二者数据进行融合,综合二者的优点,可以有效提高定位精度。通过实验表明,滤波后定位效果大大好于单独使用GPS或者DR定位。
针对路径规划本文分析研究了基于行为的运动控制算法,将其应用于室外移动机器人的导航控制中。借鉴免疫网络的原理,构建了一个行为仲裁系统,对行为单元进行协调。系统能根据外部环境动态地改变行为单元的优先级,同时考虑到反应式控制体系固有的缺陷,添加规划推理模块对系统进行推理和指导,增强系统对环境的适应能力和灵活性。为了验证路径规划算法的可行性,使用VC++编写了仿真软件并对路径规划算法进行了验证。实验结果表明,在比较理想的情况下,算法可以很好地完成机器人导航任务。在仿真的基础上,使用硬件平台对算法进行验证,并分析了实验结果。
最后对全文工作进行总结,并对研究工作的继续深入提出设想。
Autonomous mobile robot has the ability of self-planning, self -organization and adaptivity. Its goal is moving and accomplishing tasks without human assistance or changing environment. So navigation is an important part of mobile robot field. And it is a key technology of mobile robot intelligence. Although our country has made some achievements, we still fall behind some western countries. And we have few robots applied in the real world. So it is of great theoretic and engineering importance to do this research.
The main content of mobile navigation system contains mobile robot localization and path-planning. In order to enable mobile robot the abilities of aptitude and autonomy, the mobile robot navigation system is analysed and researched.
First of all, the developing history of mobile robot is introduced and the developing status of mobile robot in domestic and overseas is analysed. The main technologies of mobile robot localization and path-planning nowadays is studied . Based on the requirement, a reasonable overall design of outdoor autonomous mobile robot localization and path-planning is presented.
Then a mobile robot control program is written to apply the algorithms of navigation conveniently. The design patterns is applied in the program innovatively so the program can cope with changes easily and it is ready for running in another operating system.
After that GPS localization and DR navigation principle are analysed and researched. The error of GPS localization is large and there are areas where the GPS data cannot be received. The error of DR is initially small but will be larger and larger as the time goes. So the Kalman filter is used to combine the GPS data and DR data to integrate their advantages. It is shown by the experiment, the filter improves the localization precision greatly.
Then the behavior based motion control method is analysed and is applied in the outdoor mobile robot navigation. By using immune network principle, a behavior arbitration system is built to select behavior. The priority of behavior can be dynamically changed depending on the outside circumstances. The drawback of reactive controlling system is considered, and the planning or reasoning module is added to enhance the system’s adaptation to environment and flexibility. In order to verify the feasibility of the algorithm, a simulation program is designed in Visual C++ and the path-planning algorithm is evaluated. Experiments demonstrate that in relatively ideal condition the robot can accomplish task using the algorithm. Then the algorithm is tested on the hardware platform and the result is analysed.
In the end, a summary is made for the whole research work and the future research plan is presented.
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