摘要移动传感器网络的持续覆盖是一个以研究路径规划为主的课题。在已知的环境下规划一组已知速度和传感半径的传感器的循环覆盖路径。要求传感器能周期性的循环覆盖整个区域，并且分配不同子任务使每个传感器的覆盖周期相同，这在扫雷、清洁和灾后救援，以及监控侦察、收割庄稼等方面具有实际应用的价值。66786

    近几年来，各种类型的路径规划都在迅速的发展，移动机器人技术研究中的一个重要领域是路径规划技术，它分为基于模型的环境已知的全局路径规划和基于传感器的环境未知的局部路径规划。其中又包括许多适应不同状态的路径规划方法，如神经网络、栅格法等等。

此次研究的主要是区域覆盖，所以主要讨论一些全局路径规划的方法，但是全局路径规划也不是覆盖的路径规划，所以我们要研究的是全覆盖路径规划的子区域行走办法，并从中得出简单实用的路径规划策略。并用MATLAB进行仿真模拟。

毕业论文关键词  持续覆盖  全覆盖路径规划   子区域行走方式  matlab仿真

毕业设计说明书（论文）外文摘要

Title   study on persistent coverage control of mobile sensor                    

           network.                                                 

Abstract

Continuing coverage of the mobile sensor network,its main topic is to study the path planning. A set of known velocity sensors and sensing radius circular coverage path planning in a known environment. Sensor periodic cycle covering the entire region, and assign different subtasks of each sensor cover the same period, the value of practical application in mine clearance, cleaning and disaster relief, as well as surveillance reconnaissance, harvesting crops.

In recent years, various types of path planning in the rapid development of mobile robotics research is an important area of path planning technology, which is pided into global path planning based on the model of the environment is known and unknown sensor-based environment local path planning.  which adapt to different path planning methods, such as neural networks, grid method, and so on.

The study mainly regional coverage, it focuses on some of the global path planning method, but global path planning is not covered path planning, so we need to study the full coverage path planning sub-regional walking way, and draw simple and practical path planning strategies. Using MATLAB simulation.

Keywords  Continuing coverage  full coverage path planning  sub-regional walking way  MATLAB simulation.

目   次  

1   引言 1

  1.1  研究课题和要求2        

  1.2  主要内容和结构安排 3

  1.2.1 研究的主要内容3

  1.2.2 论文结构4

2    路径规划简介4 

2.1   全局路径规划 4 

2.1.1  可视图法5

2.1.2  拓扑法5

2.1.3  栅格法6

2.1.4  自由空间法6

2.1.5  存在障碍物约束的最优控制法6

2.1.6  神经网络法6

2.2  局部路径规划  6

2.2.1  人工势场法6

2.2.2   模糊逻辑算法8

2.2.3    神经网络法8

2.2.4   遗传算法9

2.3 全覆盖路径规划11 

2.3.1   随机式全覆盖11

2.3.2   规划式全覆盖12