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3 Augmented reality visual Interfaces in robot teleoperation Example of use of augmented reality in telerobotics are numerous in lit- erature, as regards both telemanipulation and mobile robots teleguide. This section contains a review of the current state of the art in visualization techniques for teleguide interfaces based on augmented reality and sensor fusion. Major contributions are resumed and their main points are highlighted and discussed. 19
3.1 A sensor fusion based user interface for vehicle teleoperation The work of Meier et al. [24] describes a technique of sensor fusion for mobile teleoperation which uses different sensors in a complementary manner, balancing respective points of strength and weaknesses. A brief analysis of sensor fusion for teleoperation is carried out. Sensor fusion needs to be human-oriented, and the representation of the data has to be accessible and understandable. Fusing data in a single display, rather than representing each different sensor in a different display, makes perception quicker and reduces cognitive workload. The most important kind of information which can be shown by sensor fusion to an operator who is driving a mobile robot is depth information. This work considers color intensity the most efficient way in which this kind of information can be delivered to a human; in particular, HSV color model [52] is considered to be the one which best mimics human color perception. The teleoperation system described in this paper uses a stereo vision system, a ring of ultrasonic sonars and odometric sensors; sensor data are processed by a Kalman filter. The teleoperation interface contains a display showing the video stream from the robot cameras and a bidimensional map of the environment, gradually created as an occupancy grid using Histogramic In-Motion Mapping [53]. Depth information is overlaid on the video display as a layer com- posed by differently colored pixels. Stereo having a higher angular resolution than the sonar, it is used by default to create the overlay. Instead, sonar is used in regions of the image where stereo disparity is not reliable, i.e. regions with scarce texturing or where the sonar de- tects very close objects. A grid is projected on the region of the image identified as ground, in order to improve distance estimation (figure 11a). The bidimensional map (figure 11b) is created by combining 20
Page 1 and 2: UNIVERSITÀ DEGLI STUDI DI CATANIA
Page 3 and 4: 4.5 Summary and analysis . . . . .
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: Figure 10: (a) CristalEyes shutter
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
Page 55 and 56: s, and elevated from the ground lev
Page 57 and 58: of [25] is sensitive to calibration
Page 59 and 60: Figure 25: (a) Visual artifacts cre
Page 61 and 62: 7 Laser-camera alignment and calibr
Page 63 and 64: Figure 26: Graphical representation
Page 65 and 66: Figure 27: (a) Overlay at the begin
Page 67 and 68: parameters found the calibration pr
Page 69 and 70: 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
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[29] M. Ferre, R. Aracil, and MA Sa
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[46] L. Lipton. Stereographics, Dev
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[64] OpenGL website. http://www.ope
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