论文总字数：22734字

摘 要

随着大数据、云计算和物联网技术的兴起，基于SLAM技术的无人驾驶汽车这一在交通和物流领域都有广泛应用的新技术正在越来越受人们的重视。这一新技术的运用可以大大减小交通事故的频次，更加方便人们出行，在物流行业最困难的“最后一公里”实现无人车自主上门取派件，也可以大大减轻成本。本次毕业设计，将用一个3分米长度量级的小车做一个无人汽车的模型，用SLAM技术作为主要的导航避障手段，辅以路径导航技术，完成一个无人车的基本功能。

SLAM技术适合用于无人车在城市道路路面进行建模，它一般使用激光雷达作为主要传感器获取周围环境数据，在进行一系列的数学变换后建立起环境模型，并规划到达终点的行走方案。激光雷达的波长较短，分辨率高，可以做到很小，适合在无人车这类民用的移动场景下使用。但是只用使用激光雷达再配合INS技术，既可以实现无人驾驶，INS可以提供给无人车自身的姿态变换和历程变化信息。但是INS难免会有累计误差，在远大于车体尺寸数量级的路径距离和更复杂的城市道路环境中，还需要用到GNSS导航和路径规划技术。在本次设计中，使用地图商提供的已经成型的、成熟的路径规划不失为一种省时省力的方案。

在这套路径规划做顶层设计、GNSS导航做精确定位、SLAM做具体行走方案制定的系统中，多种技术多种传感器互相配合，以提供更加精准的数据。在本次设计中，路径规划技术提供几十米到几百米量级的导航信息，SLAM自行制定几米到几十米量级的导航信息；辅助轮编码器、加速度传感器和GNSS模块可以提供车体行驶过的距离的信息，其中前二者还能提供车体转过角度的信息；INS和GNSS模块能提供车体目前坐标的信息；激光雷达和超声波、红外传感器能提供周围环境障碍物到车体距离的信息：在车体各种不同的情境下，控制器对不同传感器提供的数据取不同的权重采信，可以大大增加车体一次导航成功率，增加容错性能。

本人一直认为，所有自己做的东西，都应该体现出自己当时的最高水平和最新理念，希望本次毕业设计是一次成功的有技术参考价值的设计。

关键词：SLAM；无人驾驶汽车；地形建模与导航；路径规划

A smart car based on SLAM with synchronous positioning and navigation

abstract

With the rise of big data, cloud computing and Internet of Things technologies, unmanned vehicles based on SLAM technology, which is widely used in transportation and logistics, are receiving more and more attention. The use of this new technology can greatly reduce the frequency of traffic accidents, and make it easier for people to travel. In the most difficult "last mile" of the logistics industry, the realization of unmanned vehicles can be greatly reduced. This graduation project will use a car of 3 decimeter length to make a model of an unmanned car. SLAM technology is used as the main means of navigation obstacle avoidance, supplemented by path navigation technology to complete the basic functions of an unmanned vehicle.

SLAM technology is suitable for the modeling of unmanned vehicles on urban road pavement. It generally uses Lidar as the main sensor to obtain the surrounding environment data, establishes an environmental model after a series of mathematical transformations, and plans the walking plan to reach the end point. Lidar has a short wavelength and high resolution, and can be used very small. It is suitable for use in civil mobile scenes such as unmanned vehicles. However, only using the laser radar and INS technology can achieve unmanned driving, and the INS can provide the attitude change and history change information of the unmanned vehicle. However, INS inevitably has cumulative errors. GNSS navigation and path planning techniques are also needed in path distances that are much larger than the size of the vehicle body and in more complex urban road environments. In this design, using the established and mature path planning provided by the map merchant is a time-saving and labor-saving solution.

In this system of path planning, top-level design, GNSS navigation for precise positioning, and SLAM for specific walking plans, multiple technologies and multiple sensors work together to provide more accurate data. In this design, the path planning technology provides navigation information on the order of tens of meters to several hundred meters. SLAM develops navigation information on the order of several meters to several tens of meters; auxiliary wheel encoders, acceleration sensors and GNSS modules can provide vehicles. Information on the distance traveled by the body, the former two can also provide information on the angle of the car body; the INS and GNSS modules can provide information on the current coordinates of the car body; the laser radar and ultrasonic, infrared sensors can provide obstacles to the surrounding environment Vehicle body distance information: In different situations of the car body, the controller takes different weights to the data provided by different sensors, which can greatly increase the car navigation success rate and increase the fault tolerance performance.

I have always believed that all the things that I have designed should reflect the highest level and the latest concept at the time. I hope that this graduation project is a successful design with technical reference value.

Key words: SLAM; driverless car; terrain modeling and navigation; path planning

目录

摘要 I

abstract II

第一章 绪论 1

1.1 课题来源及其背景和意义 1

1.2 关键技术分析 1

1.3 国内外研究现状和本次设计论文的任务安排 1

1.3.1 国外研究现状 1

1.3.2 国内研究现状 1

1.3.3 本论文的任务安排 2

第二章 电路结构 3

2.1 小车模型简介 3

2.2 电源和驱动部分 3

2.2.1电源模块 3

2.2.2电机驱动模块 4

2.3 传感器数据预处理模块 5

2.3.1 PCB及其结构 5

2.3.2 部分选用的传感器 6

2.3.3 传感器数据预处理板与其他模块的交互 6

2.4 计算核心模块 6

2.5 通讯拓扑结构 6

2.6 本章小结 7

第三章 GNSS与路径规划 8

3.1 GNSS差分定位简介 8

3.1.1 GNSS基本原理 8

3.1.2 差分定位基本原理 8

3.1.3 GNSS模块与数据提取 8

3.1.4 差分纠正 9

3.2 路径规划 10

3.3 路径规划数据交互 12

3.4 INS导航可行性分析 12

3.5 差分GNSS，INS与路径规划组合导航 13

3.6 全局异常处理机制 13

3.7 本章小结 13

第四章 SLAM建模与导航 14

4.1 激光雷达简介 14

4.2 激光雷达数据的读取和解析 15

4.2.1 数据提取 16

4.2.2 极端值影响和滤波 17

4.3 激光雷达环境建模与循迹算法 17

4.3.1 迷宫循迹中的通道和障碍物的元素 18

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