哈尔滨工业大学工程硕士学位论文
Abstract
Navigating autonomously of mobile robots is a symbol of the development direction of high and new technology, which is in the forefront of the field of scientific research. And, navigating autonomously based on Simultaneous Localization and Mapping （SLAM）is a problem that has attracted a great deal of interest in mobile robotics. In order to make the indoor mobile robot more autonomous and intelligent, this topic will study the indoor navigating autonomously based on SLAM, and further study the three problems of SLAM, localization and path planning. Due to its modular design, it has many different applications such as service robots and transport robot. The completion of this thesis will promote the development of autonomous navigation in China.
Firstly, in view of the shortcomings of the traditional filter-based SLAM algorithm, a SLAM algorithm based on graph optimization is studied in this thesis, and utilizes it to estimate the pose of the robot and the location of the features. Key steps in SLAM such as data association, loopback detection, and backend optimization are analyzed. In this paper, an active SLAM technology is designed, and the active exploration method based on the boundary is used to combine the SLAM with the path planning, so that the robot can build the map of the unknown environment autonomously, so that the robot can be truly autonomous.
In addition, the basic Monte Carlo localization algorithm and adaptive Monte Carlo localization algorithm are studied. And the convergence process of localization algorithm is analyzed through simulation experiments. The global planner algorithm A* is studied and compared with other algorithms through simulation experiments to verify its superiority. A novel local path planner algorithm is applied to achieve real-time trajectory optimization, and simulation experiments are performed to verify its effectiveness. In order to navigate safely in indoor environment, the thesis presents a method for achieving 3D obstacle avoidance in indoor complex environments, which is based on the three dimensional point cloud.
Finally, all the algorithms presented in this thesis have been tested and verified in real world experiments. Active SLAM experiments prove the feasibility of active SLAM technology. By comparing and analyzing the maps obtained by the two SLAM methods, the superiority of the SLAM algorithm used in this paper is explained. A comparison of the key dimensions between the map and the actual environment verifies the accuracy of the map. Autonomous navigation experiments verify the performance of localization algorithm and path planning algorithm, and the navigation accuracy is analyzed. Through the obstacle avoidance experiment, the navigation system's 3D obstacle avoidance ability
哈尔滨工业大学工程硕士学位论文
and dynamic obstacle avoidance ability are tested. It is proved that the real-time and robust of the path planning algorithm is good.
Through the research on SLAM, localization, and path planning, this thesis has finally obtained a stable navigation system with high autonomous capabilities and high navigation accuracy.
Key words:mobile robot, indoor autonomous navigation, SLAM, localization, path planning
哈尔滨工业大学工程硕士学位论文
目录
摘要 ....................................................................................................................... I Abstract ..................................................................................................................... I I 第1章绪论. (1)
1.1 研究背景及意义 (1)
课题来源 (1)
研究背景及意义 (1)
1.2 自主导航技术综述 (2)
1.2.1 SLAM理论 (3)
1.2.2 定位技术 (4)
1.2.3 路径规划技术 (5)
1.3 自主导航关键技术的研究现状 (6)
1.3.1 SLAM算法的国内外研究现状 (6)
1.3.2 基于SLAM的导航技术国内外研究现状 (7)
1.4 主要研究内容 (9)
第2章移动机器人的系统模型及架构 (11)
2.1 引言 (11)
2.2 传感器选型及实验平台搭建 (11)
2.2.1 传感器分析 (11)
2.2.2 实验平台搭建 (13)
2.3 机器人运动模型 (14)
2.4 传感器观测模型 (15)
2.5 环境地图模型 (15)
2.6 导航系统整体架构 (16)
机器人操作系统ROS (16)
Navigation导航软件包 (17)
室内导航系统整体结构 (18)
2.7 本章小结 (20)
第3章基于图优化理论的SLAM算法研究 (21)
3.1 引言 (21)
3.2 基于图优化理论的SLAM算法研究 (21)
哈尔滨工业大学工程硕士学位论文
激光扫描匹配 (23)
闭环检测 (24)
位姿图优化 (26)
3.3 主动SLAM技术 (28)
3.3.1 基于边界的主动探索 (28)
主动SLAM技术架构 (30)
3.4 本章小结 (31)
第4章移动机器人的定位与路径规划算法研究 (32)
4.1 引言 (32)
4.2 移动机器人的定位算法研究 (32)
蒙特卡洛定位算法研究 (32)
自适应蒙特卡洛定位算法研究 (34)
定位算法仿真实验 (35)
4.3 全局路径规划算法研究 (37)
全局路径规划算法 (37)
全局路径规划算法仿真实验 (38)
4.4 局部路径规划算法研究 (39)
局部路径规划算法 (39)
基于点云的避障策略 (41)
路径规划模块仿真实验 (42)
4.5 本章小结 (43)
第5章移动机器人导航系统的实验验证 (44)
5.1 引言 (44)
5.2 室内环境的地图构建实验 (44)
主动SLAM实验 (44)
SLAM算法对比实验 (45)
地图精度分析 (47)
5.3 移动机器人的定位及自主导航实验 (48)
已知地图的定位及自主导航实验 (48)
移动机器人的导航精度分析 (49)
5.4 移动机器人的避障实验 (51)
移动机器人的静态避障实验 (51)
移动机器人的动态避障实验 (53)
哈尔滨工业大学工程硕士学位论文
5.5 本章小结 (54)
结论 (55)
参考文献 (56)
哈尔滨工业大学学位论文原创性声明和使用权限 (60)
致谢 (61)