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基於ROS2.0分散式通訊架構之智慧環境感知的多載具任務分配研究 = =...

廖楷祥

基於ROS2.0分散式通訊架構之智慧環境感知的多載具任務分配研究 = = Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	基於ROS2.0分散式通訊架構之智慧環境感知的多載具任務分配研究 =/ 廖楷祥.
Reminder of title:	Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture /
remainder title:	Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture.
Author:	廖楷祥
Published:	雲林縣 :國立虎尾科技大學 , : 民113.07.,
Description:	[10], 108面 :圖, 表 ; : 30公分.;
Notes:	指導教授: 鄭佳炘.
Subject:	Internet of Vehicles. -
Online resource:	電子資源

基於ROS2.0分散式通訊架構之智慧環境感知的多載具任務分配研究 = = Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture /
廖楷祥

基於ROS2.0分散式通訊架構之智慧環境感知的多載具任務分配研究 =Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture /Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture.廖楷祥. - 初版. - 雲林縣 :國立虎尾科技大學 ,民113.07. - [10], 108面 :圖, 表 ;30公分.

指導教授: 鄭佳炘.

碩士論文--國立虎尾科技大學電機工程系碩士班.

含參考書目.

隨著物聯網技術和人工智能的快速發展，眾多機器開始取代重複性和高強度勞動工作。機器人從早期的工業用途逐漸拓展到可以在複雜環境中執行任務的商業應用，其對環境的適應能力顯著提升。如今，多應用層面的機器人如雨後春筍般涌現，但大多數機器人依然以單機執行任務為主，多機協同工作的機器人較為稀少。因此，本論文的研究重點是探討多載具之間如何透過自主溝通進行任務分配，而非依賴人工指定任務，以提高系統的自適應性和效率。本研究首先將分析多載具間自主溝通的技術，探討其在動態環境中進行任務分配的有效性。接著，利用光學雷達的同時定位與地圖構建技術(SLAM)和Navigation2技術，提升載具的路徑規劃能力，以實現載具間的控制與監控，從而提高載具在複雜環境中的運行效率。此外，本研究還利用ROS2.0的分散式通訊架構，建立車聯網系統。該系統將載具的物件偵測和計算任務轉移至邊緣裝置進行邊緣運算，以降低載具的計算負擔，從而提升整體系統的運算效率和響應速度。邊緣運算的應用還減少了載具所需的硬體資源，降低了成本。最後，利用地圖共享之方式讓多台載具可以輕鬆或去的地圖環境資訊，不用在各自進行掃描建圖，大幅提升工作效率，在同樣的任務內容中單台執行比多台執行，更節省時間、能源。.

(平裝)Subjects--Topical Terms:

1451768
Internet of Vehicles.

基於ROS2.0分散式通訊架構之智慧環境感知的多載具任務分配研究 = = Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture /
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246 1 1 $a Research on Multi-Vehicle Task Allocation for Intelligent Environment Perception Based on ROS 2.0 Distributed Communication Architecture.
250 $a 初版.
260 # $a 雲林縣 : $b 國立虎尾科技大學 , $c 民113.07.
300 $a [10], 108面 : $b 圖, 表 ; $c 30公分.
500 $a 指導教授: 鄭佳炘.
500 $a 學年度: 112.
502 $a 碩士論文--國立虎尾科技大學電機工程系碩士班.
504 $a 含參考書目.
520 3 $a 隨著物聯網技術和人工智能的快速發展，眾多機器開始取代重複性和高強度勞動工作。機器人從早期的工業用途逐漸拓展到可以在複雜環境中執行任務的商業應用，其對環境的適應能力顯著提升。如今，多應用層面的機器人如雨後春筍般涌現，但大多數機器人依然以單機執行任務為主，多機協同工作的機器人較為稀少。因此，本論文的研究重點是探討多載具之間如何透過自主溝通進行任務分配，而非依賴人工指定任務，以提高系統的自適應性和效率。本研究首先將分析多載具間自主溝通的技術，探討其在動態環境中進行任務分配的有效性。接著，利用光學雷達的同時定位與地圖構建技術(SLAM)和Navigation2技術，提升載具的路徑規劃能力，以實現載具間的控制與監控，從而提高載具在複雜環境中的運行效率。此外，本研究還利用ROS2.0的分散式通訊架構，建立車聯網系統。該系統將載具的物件偵測和計算任務轉移至邊緣裝置進行邊緣運算，以降低載具的計算負擔，從而提升整體系統的運算效率和響應速度。邊緣運算的應用還減少了載具所需的硬體資源，降低了成本。最後，利用地圖共享之方式讓多台載具可以輕鬆或去的地圖環境資訊，不用在各自進行掃描建圖，大幅提升工作效率，在同樣的任務內容中單台執行比多台執行，更節省時間、能源。.
520 3 $a With the rapid development of IoT technology and AI, many machines have begun to replace repetitive and high-intensity labor tasks. Robots have evolved from early industrial uses to commercial applications capable of performing tasks in complex environments, significantly improving their adaptability. Nowadays, multi-application robots are emerging, but most still operate primarily as single-task units. Multi-vehicle collaborative robots are relatively rare. Therefore, this thesis focuses on exploring how multiple vehicles can communicate autonomously for task allocation, rather than relying on manually assigned tasks, to enhance system adaptability and efficiency. This study will first analyze autonomous communication technology between multiple vehicles and examine its effectiveness in dynamic task allocation. Utilizing Simultaneous Localization and Mapping (SLAM) and Navigation2 technology, the path planning capabilities of the vehicles will be enhanced for improved control and monitoring, boosting operational efficiency in complex environments. Additionally, this research employs ROS 2.0's distributed communication architecture to establish an Internet of Vehicles (IoV) system. This system transfers object detection and computation tasks to edge devices for edge computing, reducing the computational burden on vehicles and improving overall system efficiency and response speed. The use of edge computing also reduces the hardware resources required by the vehicles, lowering costs. Finally, the paper provides a detailed discussion on the advantages and disadvantages of the IoV system established with these technologies. It conducts an in-depth analysis of multi-vehicle collaborative task execution and edge computing. Based on the analysis, specific improvement plans are proposed to enhance the overall performance and practicality of the system..
563 $a (平裝)
650 # 4 $a Internet of Vehicles. $3 1451768
650 # 4 $a ROS 2.0. $3 1451767
650 # 4 $a Navigation2. $3 1418172
650 # 4 $a Simultaneous Localization and Mapping (SLAM). $3 1451766
650 # 4 $a Task allocation. $3 1451765
650 # 4 $a 車聯網. $3 1083860
650 # 4 $a 第二代機器人操作系統. $3 1418170
650 # 4 $a 同時定位與地圖構建. $3 1418169
650 # 4 $a 任務分配. $3 1451764
856 7 # $u https://handle.ncl.edu.tw/11296/wuc2m2 $z 電子資源 $2 http