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研究生:謝凱鈞
研究生(外文):Kai-Chun Hsieh
論文名稱:有效的人體軟組織拍擊運動控制於機器人拍痰與按摩療程應用
論文名稱(外文):Effective Percussive Motion Control on Human Tissue for Robotic Patting Phlegm and Therapeutic Massage
指導教授:羅仁權羅仁權引用關係
口試日期:2017-07-25
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:電機工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:英文
論文頁數:86
中文關鍵詞:照護機器人醫療型機器人機器人拍擊按摩機器人語音控制
外文關鍵詞:healthcare robotmedical robotrobotic tapping massagerobotic speech control
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按摩不僅具有放鬆肌肉、舒緩身心、促進血液流動等功效,且療效顯著又簡便安全,因此按摩成為人類流傳最久的醫療手法之一。而由於近年來老年人口增加,使得醫療照護的需求隨之增加,為了解決醫療人力不足與增進醫療品質,許多研究機構開始致力於醫療系統的自動化,而按摩的自動化療程更是研究發展重點之一。
按摩的手法非常多樣,有揉、捏、壓、拍擊等手法。其中揉、捏、壓三種按摩手法的機器人自動化,已有相當成熟的研究技術,而拍擊相較於其他手法,因其動作頻率較快許多(約0~1Hz)、力量控制不易與安全性尚有疑慮,使得其研究發展較緩慢、不成熟。因此使機器人拍擊手法更接近按摩師即為本論文著重的研究方向。為了使機器人的拍擊頻率更加接近按摩師,此論文使用了速度控制控制機器人的拍擊頻率,並透過人體軟組織的阻抗模型,計算其產生的力道。另外再透過衝力控制減少機器人與人體碰撞時產生的碰撞震盪,增加機器人於拍擊動作的穩定度。在實驗驗證方面,利用力量/力矩感測器收集按摩師與機器人的拍擊力量與時間資訊,再透過無時間壓縮的波形相似度分析,算出兩者波形之間的相似度,實驗結果顯示出兩者間的相似度達到0.84至0.89。
除了單純的按摩拍擊手法外,此論文更將機器人末端軸替換成拍痰杯,藉由拍擊動作實施拍痰醫療手法,利用空氣振動原理使堆積在肺部的痰液鬆動,在此除了利用上述的波形相似度分析,額外利用音頻分析當作實驗驗證,更加佐證機器人於拍痰應用上的可行性。
此外,此論文也將語音與機器人結合,藉由語音功能,增加人機互動,以及藉由語音的控制,使受按摩者能於按摩途中對機器人下達命令,增加機器人按摩的安全性與方便性。
Massage is one of the oldest and most welcomed therapeutic methods because of its significant effectiveness and simple implement. It can relax muscles, release the body and mind, and improve blood circulation. In recent years, due to the increment of elderly people, the medical care becomes a more and more important issue in the society. There are many institutions committed to developing the medical system automation, in order to solve the shortage of caregivers and enhance healthcare quality. The massage therapy automation is also one of the focuses of development.
Kneading, pinching, pressure and tapping are four common massage techniques. This thesis focuses on tapping motions since few theses mention it. Unlike the other three techniques, tapping needs a high-frequency repeated motion whose frequency is about 1-2Hz. This thesis exploits speed control to manipulate its tapping frequency and calculate the force through the human body impedance model. The contact detection is developed to reduce the contact time and ensure the stability in each tapping motion. This thesis also adds tapping phlegm applications by replacing the end-effector of the robot with a phlegm cup, since these two motions are alike. With the phlegm cup, phlegm in the lungs can be loosened by tapping the human back. Furthermore, the author combines the robot with the speech control to improve the human-robot interaction and provide additional safety and convenience for users.
In the experiments, the force/torque sensor and the microphone are utilized to collect the force-time and audio data. Then, the similarity between masseur and robot with and without using the phlegm cup while massaging on the subject’s back are calculated through waveform similarity and audio similarity. The results show that the similarity has reached 84 to 89 percent which is almost the same as the masseur massage tapping motion.
誌謝 I
中文摘要 II
ABSTRACT III
TABLE OF CONTENTS IV
LIST OF FIGURES VI
LIST OF TABLES VIII
CHAPTER 1 INTRODUCTION 1
1.1 MOTIVATION AND OBJECTIVES 1
1.1.1 Motivation 1
1.1.2 Objectives 2
1.2 LITERATURE REVIEW 4
1.2.1 4 DOFs Manipulator 4
1.2.2 6 DOFs Manipulators 6
1.2.3 7 DOFs Manipulator 8
1.2.4 Multi-fingered Robot Hands 9
1.3 THESIS ORGANIZATION 11
CHAPTER 2 THE HARDWARE AND THE SYSTEM OVERVIEW 12
2.1 THE ANTHROPOMORPHIC DUAL ARM ROBOT 12
2.1.1 Mechanism Design 12
2.1.2 Mechanism Design of Robot Arms 13
2.2 FORCE TORQUE SENSOR 16
2.3 KINEMATICS ANALYSIS 18
2.4 SYSTEM STRUCTURE 22
2.5 SOFTWARE ARCHITECTURE 30
CHAPTER 3 THE PERCUSSIVE MASSAGE AND CONTROL TECHNIQUES 32
3.1 MASSAGE TECHNIQUES DEFINITION 32
3.1.1 Rubbing 32
3.1.2 Pressing 33
3.1.3 Tapping 34
3.1.4 The Comparison in Three Techniques 35
3.2 CARTESIAN IMPEDANCE CONTROL 35
3.3 ON-LINE TRAJECTORY GENERATOR 38
3.4 GRAVITY COMPENSATION 41
3.5 CARTESIAN SPACE TEACH & PLAY 43
3.6 CONTACT DETECTION 45
3.7 FORCE FEEDBACK WITH THE CONCEPT OF VIRTUAL POINT 48
CHAPTER 4 HUMAN-ROBOT INTERACTION WITH SPEECH CONTROL 52
4.1 SPEECH RECOGNITION AND TEXT TO SPEECH 53
4.1.1 Speech Recognition 53
4.1.2 Text to Speech 54
4.2 NATURAL LANGUAGE UNDERSTANDING 55
4.3 SPEECH-ROBOT COMMUNICATIONS 58
4.4 SOFTWARE ARCHITECTURE 59
CHAPTER 5 EXPERIMENTAL RESULTS 62
5.1 EXPERIMENT SET UP 62
5.2 SINGLE ROBOTIC TAPPING EXPERIMENT 64
5.3 COMPLETED ROBOTIC TAPPING EXPERIMENT 67
5.4 PATTING PHLEGM APPLICATION 69
5.5 SPEECH CONTROL AND HUMAN ROBOT INTERACTION 73
5.6 DISCUSSION 79
CHAPTER 6 CONCLUSIONS AND CONTRIBUTIONS 80
6.1 CONCLUSIONS AND CONTRIBUTIONS 80
6.2 FUTURE WORKS 81
REFERENCES 82
VITA 86
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