陳明新臺灣大學：機械工程學研究所李俊賢Li, Jyun-SianJyun-SianLi2007-11-282018-06-282007-11-282018-06-282006http://ntur.lib.ntu.edu.tw//handle/246246/61202由於影像伺服追蹤系統受限於攝影機較低的取樣速度，造成整體追蹤性能不佳。在本文中，我們提出適應性預測及內插方法。藉由此方法，得到高取樣速度下目標物運動軌跡的虛擬取樣位置，並配合伺服馬達做高速度取樣的追蹤控制，以改善整體追蹤效能。 結果顯示，使用高階的適應性線性軌跡模型做預測，配合曲線內插方法可估測出較準確的物體運動軌跡。一個低取樣速度系統，在加入預測性內插後，其追蹤效能近似高取樣速度系統。The tracking performance of visual servo system is limited by the low sampling rate of camera. In this thesis, we present an adaptive prediction and interpolation method. Through this method, we could get the virtual sampling values of motion trajectory of target at high sampling rate. According to the high sampling rate trajectory, the servo motor could perform high speed tracking control. The results show that we could get more accurate motion trajectory by using high order linear model for adaptive estimation. In addition, the tracking performance of low sampling rate system in cooperated with the predictive interpolation will approach that of high sampling rate system.CATALOG 摘要 I Abstract II Chapter 1 Introduction 1 1.1 Visual servo system 1 1.2 Problem of visual servo system 3 1.3 Thesis organization 4 Chapter 2 Estimation of motion Trajectory 6 2.1 Recursive least squares and projection algorithm 6 2.1.1 Regression form 6 2.1.2 Recursive least squares estimation 8 (a) Recursive least squares algorithm 8 (b) Recursive least squares algorithm with exponential forgetting 9 (c) Recursive projection algorithm 9 2.2 Model based prediction 10 2.3 Curve fitting 11 2.4 Prediction of motion trajectory 13 2.4.1 A linearized Pendulum model 13 2.4.2 Prediction with different order model 16 (a) order 3 16 (b) order 5 20 (c) order 7 24 (d) Comparison of different methods with different order 28 2.5 Interpolation 30 2.5.1 Linear Interpolation 31 2.5.2 Curve Interpolation 32 Chapter 3 The structure of visual servo system 36 3.1 Overview of visual servo system 36 3.2 Build the model of visual servo system 37 3.3 Controller design 39 3.3.1 Continuous-time controller design 39 3.3.2 Discrete-time equivalent controller 43 3.4 Predictive interpolation 49 3.4.1 The structure of Predictive interpolation 49 3.4.2 Comparison of simulation 53 3.4.3 The problem about delay of image processing 57 Chapter 4 Experiment 61 4.1 Hardware and software 61 4.2 Calibration of camera parameters 63 4.3Target Detection and Graphic User Interface(GUI) 71 4.3.1 Target Detection Methods 71 4.3.2 Introduction of Graphic User Interface (GUI) 77 4.4 Tracking performance comparison 82 Chapter 5 Discussion and future work 86 Reference 88 FIGURE Figure 2. 1 Pendulum model 13 Figure 2. 2 Continuous motion trajectory in x direction 14 Figure 2. 3 Sampled trajectory signal 15 Figure 2. 4 Prediction with LS Exp (order3) 17 Figure 2. 5 Prediction with projection (order3) 18 Figure 2. 6 Prediction with curve fitting (order3) 19 Figure 2. 7 Prediction with LS Exp (order5) 21 Figure 2. 8 Prediction with Projection (order5) 22 Figure 2. 9 Prediction with curve fitting (order5) 23 Figure 2. 10 Prediction with LS Exp (order7) 25 Figure 2. 11 Prediction with projection (order7) 26 Figure 2. 12 Prediction with curve fitting (order7) 27 Figure 2. 13 Prediction error comparison of LS Exp with different order 28 Figure 2. 14 Prediction error comparison of Projection with different order 28 Figure 2. 15 Prediction error comparison of curve fitting with different order 29 Figure 2. 16 Interpolation 30 Figure 2. 17 Linear interpolation 31 Figure 2. 18 Interpolation with linear method 32 Figure 2. 19 Curve interpolation 33 Figure 2. 20 (a)(b) 34 Figure 2. 21 Interpolation with curve method 35 Figure 2. 22 Interpolation error comparison 35 Figure 3. 1 36 Figure 3. 2 Geometry relationship with pinhole perspective projection 38 Figure 3. 3 Block diagram of visual servo system 39 Figure 3. 4 Continuous version of visual servo system 39 Figure 3. 5 Root locus of the system with PI controller 40 Figure 3. 6 Step response with kp=50 41 Figure 3. 7 Ramp response with kp=50 42 Figure 3. 8 Sampled data system with digital control 44 Figure 3. 9 Step response with different sampling rate 44 Figure 3. 10 Root locus in Z-domain with 0.5sec sampling period 45 Figure 3. 11 Root locus in Z-domain with 0.1sec sampling period 46 Figure 3. 12 Root locus in Z-domain with 0.05sec sampling period 46 Figure 3. 13 Root locus in Z-domain with 0.01sec sampling period 47 Figure 3. 14 Tracking errors of different sampling periods with ultimate gains applied 48 Figure 3. 15 The original structure of visual servo system 49 Figure 3. 16 visual servo system with the predictive interpolation type 1 50 Figure 3. 17 visual servo system with the predictive interpolation type 2 51 Figure 3. 18 virtual loop system 52 Figure 3. 19 Visual servo system with 0.1 sec sampling period 53 Figure 3. 20 Visual servo system with 0.01 sec sampling period 53 Figure 3. 21 Visual servo system with predictive interpolation 54 Figure 3. 22 Tracking simulation with 0.1sec sampling rate 54 Figure 3. 23 Tracking simulation with 0.01sec sampling rate 55 Figure 3. 24 Tracking simulation with interpolation 55 Figure 3. 25 Interpolation error 56 Figure 3. 26 57 Figure 3. 27 58 Figure 3. 28 58 Figure 3. 29 60 Figure 4. 1 61 Figure 4. 2 62 Figure 4. 3 63 Figure 4. 4 65 Figure 4. 5 66 Figure 4. 6 66 Figure 4. 7 69 Figure 4. 8 71 Figure 4. 9 72 Figure 4. 10 72 Figure 4. 11 73 Figure 4. 12 73 Figure 4. 13 (a)(b)(c) 74 Figure 4. 14 (a)(b) 75 Figure 4. 15 (a)(b) 75 Figure 4. 16 (a)(b) 75 Figure 4. 17 76 Figure 4. 18 76 Figure 4. 19 77 Figure 4. 20 78 Figure 4. 21 79 Figure 4. 22 79 Figure 4. 23 80 Figure 4. 24 81 Figure 4. 25 81 Figure 4. 26 82 Figure 4. 27 82 Figure 4. 28 (a)(b) 83 Figure 4. 29 Tacking without prediction 84 Figure 4. 30 Tacking without prediction 84 Figure 4. 31 Tacking with prediction 85 Figure 4. 32 Tacking with prediction 85 TABLE Table 4. 1 67 Table 4. 2 68 Table 4. 3 702682848 bytesapplication/pdfen-US影像伺服適應控制虛擬取樣visaul servoadaptive controlvirtual samplingthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/61202/1/ntu-95-R93522818-1.pdf