| DC 欄位 |
值 |
語言 |
| DC.contributor | 資訊工程學系在職專班 | zh_TW |
| DC.creator | 林顯逢 | zh_TW |
| DC.creator | Hsien-Feng Lin | en_US |
| dc.date.accessioned | 2020-6-24T07:39:07Z | |
| dc.date.available | 2020-6-24T07:39:07Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=107552013 | |
| dc.contributor.department | 資訊工程學系在職專班 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 光達 (LiDAR) 是近年來受到矚目的一種 SLAM 技術，原因是它具有高量測距離、高精度、高辨識度等優點，可滿足自主行動機器人 SLAM 的需求。但 LiDAR 存在的問題是它的製造工藝困難且調校費時不易被大量生產，導致價格居高不下，而影響了 SLAM 系統的應用推廣。有鑑於當前許多學術論文或市售產品用於 SLAM 的方法和技術，多數是基於使用LiDAR及各自開發的演算法來實現，這除了提高產品的成本之外也大幅增加系統開發者的研發週期。
本研究以 MIAT 方法論設計了一個低成本且高效能的 LIF-SLAM 系統，它是基於一個低成本的距離感測器陣列和一個低成本的九軸姿態感測器，利用它們融合的互補特性來提升整個系統的SLAM建圖性能，同時在開源軟體 ROS 中選用穩健性最高、且能構建具有最小誤差地圖的 cartographer SLAM 演算法來整合至本系統，以縮短系統開發者的研發週期。
在系統整合實驗中，LIF-SLAM 系統生成的SLAM地圖與 ground truth 誤差僅為 2.3829%，而市售產品 Neato XV-11 系統的誤差為 33.6774%，該結果顯示本系統具有更好的建圖性能且更貼近真實世界中的場景。本研究證明了 LIF-SLAM 系統在室內局部空間範圍小於4米的條件下，能夠替代 LiDAR 作為環境探勘和姿態定位的硬體裝置，且預期可大幅降低製造工藝和調校上的難度，也不需要嚴苛的組裝環境，具有更佳的使用壽命，同時也縮短了系統開發者對產品的研發週期。 | zh_TW |
| dc.description.abstract | Light detection and ranging (LiDAR) is a simultaneous localization and mapping (SLAM) technology that has attracted considerable research attention in recent years. LiDAR, which has the advantages of a long detection distance, high precision, and high recognition, satisfies the SLAM needs of autonomous mobile robots. However, LiDAR is costly because of manufacture difficulties and the requirement of time-consuming adjustments. These drawbacks hinder the mass production of LiDAR devices and thereby affect the application and promotion of SLAM systems. Various researchers have used LiDAR and self-developed algorithms to realize SLAM. This method considerably increases the length of the research and development cycle in system development.
This study used the MIAT methodology to design a low-cost and high-performance LIF-SLAM system based on a low-cost distance sensor array and low-cost nine-axis posture sensor. This system was combined with the cartographer SLAM algorithm in the ROS open-source software. The adopted methodology considerably decreased the research and development cycle in system development.
The results of the system integration experiment revealed that the LIF-SLAM system generated a SLAM map with an error of only 2.3829% compared with the ground truth (the error of the Neato XV-11 system was 33.6774%). The designed LIF-SLAM system provides high SLAM performance in real-world environments. This study indicates that the designed system can replace LiDAR as a hardware environmental exploration device in an indoor space with a range of less than 4 m. The designed system substantially reduces the difficulties in the manufacturing process and adjustments. It does not require a rigorously controlled assembly environment and exhibits a relatively high usage lifespan and mapping performance; thus, the product research and development period required by system developers is shortened. | en_US |
| DC.subject | 光達 | zh_TW |
| DC.subject | 距離感測器陣列 | zh_TW |
| DC.subject | 九軸運動感測器 | zh_TW |
| DC.subject | 機器人作業系統 | zh_TW |
| DC.subject | cartographer SLAM | zh_TW |
| DC.subject | MIAT方法論 | zh_TW |
| DC.subject | LiDAR | en_US |
| DC.subject | Distance sensor array | en_US |
| DC.subject | Nine-axis motion sensor | en_US |
| DC.subject | ROS | en_US |
| DC.subject | cartographer SLAM | en_US |
| DC.subject | MIAT methodology | en_US |
| DC.title | 基於光達和九軸運動感測器融合的SLAM | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | SLAM Based on Fusion with LiDAR and 9-Axis Motion Sensor | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |