臺灣博碩士論文加值系統

隨著電子製程技術的進步，帶動電腦資訊產業蓬勃發展，使得整合性產品的開發日新月異，相對也使得機器人產業發展快速成長，近年來透過嵌入式系統及積體電路等應用，結合網際網路資訊環境，迅速發展成無所不在的計算網路環境，使得機器人提供多樣化服務，也讓機器人廣泛並成它a運用在釵h領域上，進而提升人們生活品質並保障生命安全。
本論文研究兩個主題在研發以網際網路為基礎之人與機器人互動平台以及電源管理系統。智慧型行動機器人中的系統是採用分散式架構，而子系統中的溝通及協同合作均透過核心系統控制，各個子系統可以依據自己的智慧理論來完成核心的指派工作，包括整合控制、命令裁決、行為切換以及資源分享皆是透過核心來處理調派，人與機器人互動平台以此為作為架構，使用觸控螢幕、個人數位助理、物理感測平台及個人電腦等裝置，由服務代理人即時提供網路資訊及環境資訊，運用動畫軟體技術提供多元情境感知的動態多媒體服務及親和的使用者介面，讓使用者便利地與機器人產生互動，提升整體機器人的弁鄔妡P價值性。同時為了使機器人提升續航力，我們也研製電源管理系統，採用支持向量迴歸演算法，改善傳統庫倫電流法、電動勢法以及類神經網路法等缺點，準確預估電池殘電量，並由電源管理代理人決策是否關閉非必要裝置電源，並開始執行入塢充電任務。
本論文建立人與機器人互動架構及電源管理系統，用來對機器人系統做一有效的操作與監控，最後展示機器人應用情境，結果顯示所提出架構及系統確實有預期的效益。

In recent years, significant advances in the semiconductor technology used to electronics, contributed to the development and prosperity of computer science and information industrial. Therefore, the integrated design was never-ending changes and help drive robotics innovation. Furthermore, the explosive growth and development of the integrated circuit and embedded system technologies, with prevalence of electronic information become ubiquitous computing environments, enabling robot advance provides variety of services to increase quality of life.
The two main topics of this thesis are to develop network-based multimodal Human-robot Interactions (HRI) and power management system (PMS). The autonomous mobile robot is basically decentralized architecture, all of service agents use intelligent algorithm to achieve objectives commanded by kernel, which processes communicate with each other and coordinate their activities. HRI based the same Inter-process Communication (IPC) mechanisms with service agents, and combine with touch panel, personal digital assistant and etc of peripheral devices to enrich interaction and convenient for people. In addition, we considerate to robot effective battery life working and designed power management system, which using Supper Vector Regression (SVR) to predict State-of-Charge (SoC) of lead-acid battery. The method improves shortcoming of column counting approach, electromotive force approach and neural network. According to SoC of battery, PMS will make decision to docking to charging station.
We have constructed network-based multimodal HRI and implement PMS for autonomous mobile robot. Finally, we demonstrated scenarios and perform very well in our laboratory.

誌 謝 I
中文摘要 II
Abstract III
Acknowledgments IV
Table of Contents V
List of Figures IX
List of Tables XI

Chapter 1. Introduction 1
1.1 Era of Ubiquitous Computing 1
1.2 Motivation and Objectives 2
1.3 Major Issues and Challenges 4
1.4 Market Issues 6
1.4.1 Market Pull and Product Opportunities 6
1.4.2 Market Potential of the Service Robot 9
1.5 Thesis organization 10

Chapter 2. Literature Review 12
2.1 Review of Intelligent Robot System 12
2.1.1 GuardRobo (Security Robot) 13
2.1.2 IROBI (Programmable Robot Base for Entertainment and Education) 14
2.1.3 RP-7 (Remote-Presence Medical Robot) 17
2.1.4 Twendy-One (Service Robot) 19
2.2 Review of Network-based Human-Robot Interactions through the Internet 20
2.2.1 Usability Inspection from HCI to HRI 21
2.2.2 Evolutionary Role Model of Service Robots 23
2.2.3 Category of the Networked Intelligent Robots 25
2.3 Review of Cognitive Architecture for Human-Robot Interactions 28
2.3.1 Multiple Agent-based Architecture Designed 29
2.3.2 Case-Based Reasoning Approach 31
2.3.3 Script Design Framework 33

Chapter 3. Design of Multisensor-based Service Robot 34
3.1 Introduction 34
3.2 System Architecture 35
3.2.1 H/W Configuration 35
3.2.2 S/W Configuration 38
3.3 Distributed Artificial Agents 40
3.3.1 Client-Server Computing 42
3.3.2 Types of Service Agents 47
3.4 Multi-agent Coordination 56
3.5 Robot Sensing and Sensors 57
3.5.1 Multi-Sensor Fusion and Integration 57
3.5.2 General Classification of Sensors 59
3.5.3 Sensors Used in Robot 60

Chapter 4. Power Management Using Support Vector Regression Approach 62
4.1 Introduction 62
4.2 H/W Configuration of Power Management Unit 64
4.3 Related Work 67
4.3.1 Battery Technology 68
4.3.2 Coulomb Counting Approach 68
4.3.3 Electromotive force(EMF) Approach 69
4.3.4 Levenberg-Marquardt Back-Propagation (LMBP) 70
4.4 Support Vector Regression 71
4.5 Experimential Results 74

Chapter 5. Design of Network-based Multimodal Human-robot Interactions Originated from Computers 78
5.1 Human-robot Interaction Framework 79
5.2 Automatic Speech Recognition (ASR) 85
5.3 Physical Computing Devices 90
5.4 Hand Gesture Expression 92
5.5 Remote Supervisory 93
5.6 Expressive Modalities 95
5.7 Applying Semantic Web Services 97

Chapter 6. Integrating Context Awareness with Service Robot 101
6.1 Concept of Context-awareness 101
6.2 Remote Healthcare of Scenarios 102
6.3 Security Guard of Scenarios 107
6.4 Collaborate with Multimedia System of Scenarios 109
Chapter 7. Conclusions and Contributions 112
7.1 Conclusions 112
7.2 Contributions 113
Reference 115

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