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Contents 1 Introduction 3 2 Background 7 2.1 Augmented reality . . . . . . . . . . . . . . . . . . . . . 7 2.2 Pinhole camera model . . . . . . . . . . . . . . . . . . . 10 2.3 Stereoscopic visualization . . . . . . . . . . . . . . . . . . 14 3 Augmented reality visual Interfaces in robot teleoperation 19 3.1 A sensor fusion based user interface for vehicle teleoperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.2 Fusion of laser and visual data for robot motion planning and collision avoidance . . . . . . . . . . . . . . . . . . . 22 3.3 Using augmented reality to interact with an autonomous mobile platform . . . . . . . . . . . . . . . . . . . . . . . 23 3.4 Improved interfaces for human-robot interaction in ur- ban search and rescue . . . . . . . . . . . . . . . . . . . . 25 3.5 Ecological interfaces for improving mobile robot teleoperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.6 Egocentric and exocentric teleoperation interface using real-time, 3D video projection . . . . . . . . . . . . . . . 29 3.7 Summary and analysis . . . . . . . . . . . . . . . . . . . 31 4 Previous work on 3MORDUC teleoperation 33 4.1 The 3MORDUC platform . . . . . . . . . . . . . . . . . 34 4.2 Mobile robotic teleguide based on video images . . . . . 37 4.3 Depth-enhanced mobile robot teleguide based on laser images . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.4 Augmented reality stereoscopic visualization for intuitive robot teleguide . . . . . . . . . . . . . . . . . . . . . . . 41 1
4.5 Summary and analysis . . . . . . . . . . . . . . . . . . . 43 5 Proposed method: AR stereoscopic visualization 44 5.1 Core idea and motivation . . . . . . . . . . . . . . . . . . 44 5.2 Research development strategy . . . . . . . . . . . . . . 46 6 Effective multi-sensor visual representation 52 6.1 Visualization of laser data through AR features . . . . . 52 6.2 Detection of discontinuities . . . . . . . . . . . . . . . . . 56 6.3 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 7 Laser-camera alignment and calibration 60 7.1 Laser-camera model . . . . . . . . . . . . . . . . . . . . . 60 7.2 Feedback-based calibration procedure . . . . . . . . . . . 62 7.3 Comparison with automatic calibration . . . . . . . . . . 63 7.4 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 8 Integrating 3D Graphics with image processing 67 8.1 Edge detection algorithm . . . . . . . . . . . . . . . . . . 67 8.2 Nearest edges discovery . . . . . . . . . . . . . . . . . . . 70 8.3 Improving alignment with edges . . . . . . . . . . . . . . 73 8.4 Improving reliability with edges . . . . . . . . . . . . . . 73 8.5 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 9 Stereoscopic augmented reality 79 9.1 Stereo AR alignment . . . . . . . . . . . . . . . . . . . . 79 9.2 NEP correspondence and suppression . . . . . . . . . . . 80 9.3 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 10 Conclusions 86 References 88 2
Page 1: UNIVERSITÀ DEGLI STUDI DI CATANIA
Page 5 and 6: ing telerobotic systems continues t
Page 7 and 8: tion. Section 3 describes the state
Page 9 and 10: • to be registered in 3D (that is
Page 11 and 12: lay in advance. In video-based AR s
Page 13 and 14: The point R at the intersection of
Page 15 and 16: 2.3 Stereoscopic visualization A st
Page 17 and 18: disparity and will be seen as if th
Page 19 and 20: Figure 10: (a) CristalEyes shutter
Page 21 and 22: 3.1 A sensor fusion based user inte
Page 23 and 24: 3.2 Fusion of laser and visual data
Page 25 and 26: the edges of the graph. Once the ro
Page 27 and 28: Figure 13: Modified INEEL interface
Page 29 and 30: enefit from having both video and m
Page 31 and 32: mesh of the environment onto the le
Page 33 and 34: of monocular depth cues. Besides, w
Page 35 and 36: 4.1 The 3MORDUC platform The 3MORDU
Page 37 and 38: Figure 18: The STH-MDCS2-VAR-C ster
Page 39 and 40: higher mean speeds. Main points:
Page 41 and 42: tion permits a significant decrease
Page 43 and 44: Figure 20: (a) Proximity planes ove
Page 45 and 46: 5 Proposed method: AR stereoscopic
Page 47 and 48: 5.2 Research development strategy T
Page 49 and 50: Several approaches that permit an a
Page 51 and 52: the left and the right image. Real
Page 53 and 54:
6 Effective multi-sensor visual rep
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s, and elevated from the ground lev
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of [25] is sensitive to calibration
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Figure 25: (a) Visual artifacts cre
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7 Laser-camera alignment and calibr
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Figure 26: Graphical representation
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Figure 27: (a) Overlay at the begin
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parameters found the calibration pr
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to the maximum value (white). Inten
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variate the single parameters while
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Figure 31: Unprojection of the edge
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Figure 32: (a) Alignment using feed
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Since the last case is rather unlik
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(see the box on the left of figure
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elonging to the same model may have
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could contain artifacts which the o
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cially useful to eliminate vertical
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10 Conclusions This work has presen
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References [1] B. Davies. A review
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B. MacIntyre. Recent advances in au
Page 93 and 94:
[29] M. Ferre, R. Aracil, and MA Sa
Page 95 and 96:
[46] L. Lipton. Stereographics, Dev
Page 97:
[64] OpenGL website. http://www.ope
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