研究生: |
關永念 Yong-Nian Guan |
---|---|
論文名稱: |
基於雷射測距儀之四周環境即時定位與地圖構建 Laser Scanner Based Simultaneous Localization and Mapping in an Open Environment |
指導教授: |
施慶隆
Ching-Long Shih |
口試委員: |
李文猶
Wen-Yo Lee 黃志良 Chih-Lyang Hwang |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電機工程系 Department of Electrical Engineering |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 中文 |
論文頁數: | 58 |
中文關鍵詞: | 移動機器人 、掃地機器人 、雷射測距儀 、即時定位與地圖構建 、里程計 |
外文關鍵詞: | Mobile Robot, Robot Vacuum, LiDAR, Simultaneous Localization and Mapping, Odometer |
相關次數: | 點閱:667 下載:23 |
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本論文實現雙台機器人即時定位與地圖構建系統。環境由四周皆為牆壁且無障礙物所組成,機器人於環境中移動並同時建置地圖。此多台機器人系統分為移動機器人控制器與伺服器兩部分。移動機器人使用雙驅動輪搭配PIC微控制器與樹梅派,機器人的移動策略採用掃地機器人中兩種方法:隨機漫步法以及摸牆法,論文中部份實驗將比較兩種方法及不同環境之差異。伺服器則架設於另一個樹梅派上,此伺服器負責地圖合成與接收機器人回傳的封包,封包資料中含有雷射測距儀資料與位置資訊,並將各台機器人回傳的資料處理後並儲存於陣列結構當中;伺服器也同時偵測機器人是否互相偵測到對方,當偵測到對方時,伺服器會透過相互之關係立刻地將地圖合併。本文後段將會對單台機器人與雙台機器人花費時間以及覆蓋率做比較。未來也希望能支援更多台車共同建構地圖,並藉由SLAM讓機器人知道此地方是否曾經來過,使機器人能毫無死角地巡航各個角落。
This thesis describes an on-line system for dual-robot simultaneous localization and mapping(SLAM). The environment consists of walls without obstacle. The mobile robots move in the environment and create the map at the same time. There are two subsystems in this multi-robot system. One is mobile robot controller and the other is server system. The mobile robot control system is an accurate differential drive mobile robot controlled by PIC controller and Raspberry Pi. The moving algorithms of robots are based on autonomous vacuum cleaner: random walking algorithm and wall following algorithm. Several experiments are conducted to compare above two algorithms in different environments. Second, the server also implemented on Raspberry Pi receives the message packet from all robot and merges the maps. The packets consist of laser data and location information. This server first parses the messages and records the map on the grid structure. Next, the server detects whether another robot is present or not. The server will merge the map immediately after it found nearby robots. Finally, discuss the cost time and the completion performance of the map. In the future, multi-robot integrated with SLAM can know the place where has not been there, and improve the software to avoid collision with objects in rooms and rooms of other shapes.
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