1 (a) Start (b) Bank 2. 1 (c) Mold (d) Complete Fig. 1: Process of banking by excavator 2.1 Top of slope Face of slope 1 1(a) 1(b) 1(c) 2 Face of slop

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1 Evaluation of Images for Teleoperated Excavator in Banking Yushi MORIYAMA (The University of Tokyo), Hiromitsu FUJII (The University of Tokyo), Yusuke TAMURA (The University of Tokyo), Hiroshi YAMAKAWA (The University of Tokyo), Hisaomi MIKI (Fujita Co.,Ltd), Takumi CHIBA (Fujita Co.,Ltd), Shingo YAMAMOTO (Fujita Co.,Ltd), Kazuhiro CHAYAMA (KOKANKYO Engineering Co.,Ltd), Keiji NAGATANI (The University of Tokyo), Atsushi YAMASHITA (The University of Tokyo), and Hajime ASAMA (The University of Tokyo) Abstract : When any disaster occurs, teleoperation of construction machineries enables operators to keep safe. However, work efficiency of teleoperation is less than that of usual operation with operators in machineries. One of the reason is that operators of construction machineries are not able to receive appropriate images what are contorolled to provide work report by camera-operators. To automate offering images like the way experienced camera-operators do is effective because they can offer images what operators of construction machinery require. In order to do that, a quantitative evaluation of images is essential. We focused on banking by teleoperated excavator and sorted requirements for images. In addition to this, we proposed an evaluation method of requirements by using images and LiDAR. Based on the experimental results, the proposed method can evaluate and classify images according to requirements. 1. [1][2] 3 [1][3][4] [5] [6][7] 6 [4] 1 [8] Kamezaki [9] 3

2 1 (a) Start (b) Bank 2. 1 (c) Mold (d) Complete Fig. 1: Process of banking by excavator 2.1 Top of slope Face of slope 1 1(a) 1(b) 1(c) 2 Face of slope Top of slope Foot of slope (1) (2) Foot of slope Fig. 2: Shape of embankment and name of parts

Camera Image data LiDAR 3D data Marker Requirement 1. E ver Requirement 2.

3: Schematics of the proposed method algorithm O u Working point Fig.

point a,b O l w 2, h 2 u Face of slope v w,h Fig.

4: Angle used for evaluating requirement 1 3 Light Detection and Ranging

3 Camera Image data LiDAR 3D data Marker Requirement 1. E ver Requirement 2. E cen Section Section Evaluation E = E ver E cen Section Fig. 3: Schematics of the proposed method algorithm O u Working point Fig. 5: Specifying the working point used for evaluating requirement 2 Working point a,b O l w 2, h 2 u Face of slope v w,h Fig. 6: length l used for evaluating requirement 2 v Fig. 4: Angle used for evaluating requirement 1 3 Light Detection and Ranging (LiDAR) u v = 90 = 90 = 90 E ver E ver = sin (1) a, b (w, h) 6 ( l = a w ) ( 2 + b h ) 2 (2) 2 2 e p l 1 1

O u Camera LiDAR k d w 2, h 2 v w,h Fig.

1 d k 7 d = w 2 sin + ( h 2 + k ) cos (4) e l e p d 1 1 4 0 e l = 1 2d w2 + h 2 (5) e p e l E

4 O u Camera LiDAR k d w 2, h 2 v w,h Fig. 7: length d used for evaluating requirement e p = 1 2l w2 + h 2 (3) 3.1 d k 7 d = w 2 sin + ( h 2 + k ) cos (4) e l e p d e l = 1 2d w2 + h 2 (5) e p e l E cen E ver e p e l E cen e p+e l 2 (e p e l 0) E cen = 0 (e p e l = 0) Camera and LiDAR Fig. 8: Experimental system Face of slope Manipulator (Using as Excavator) Fig. 9: Experimental image E = E ver E cen (6) LiDAR 8 Point Grey Research Grasshopper3 GS3-U3-41C6C-C LiDAR Velodyne HDL-32e LiDAR MOTOMAN-HP3J 9 1/12 2.3

(a) Face of slope is displayed in a vertical direction and working point is displayed nearby the center.

(c) Face of slope is displayed in a horizontal direction and working point is displayed far from the center. Fig.

displayed. (a) = 101.7, e p = 77.7, and e l = 92.5 (b) = 131.3, e p = 76.8, and e l = 80.1 (c) = 162.4, e p = 57.8, and e l = 57.

Green and blue areas are planes, the yellow line is Face of slope and the red point is working point. 4.

5 (a) Face of slope is displayed in a vertical direction and working point is displayed nearby the center. (b) Face of slope is displayed in a slanting direction and working point is displayed nearby the center. (c) Face of slope is displayed in a horizontal direction and working point is displayed far from the center. Fig. 10: Evaluated images in this experiment (d) Face of slope is displayed in a vertical direction and working point is not displayed. (a) = 101.7, e p = 77.7, and e l = 92.5 (b) = 131.3, e p = 76.8, and e l = 80.1 (c) = 162.4, e p = 57.8, and e l = 57.8 (d) = 98.2, e p = 0.00, and e l = 97.1 Fig. 11: Analyzed images in this experiment. Green and blue areas are planes, the yellow line is Face of slope and the red point is working point (a) 10(b) 10(c) 10(d) 11 1 E ver 10(a) 10(d) 10(b) 10(c) E cen 10(a) 10(b) 10(a) 10(c) Table 1: Evaluation results Evaluation (a) (b) (c) (d) E ver E cen E (d) 4 0 E 10(a) 10(c) 10(d) 0

6 5. LiDAR 3 3 [1],,, vol. 33, no. 6, pp , [2] K. Chayama, A. Fujioka, K. Kawashima, H. Yamamoto, Y. Nitta, C. Ueki, A. Yamashita and H. Asama: Technology of Unmanned Construction System in Japan, Journal of Robotics and Mechatronics, vol. 26, no. 4, pp , [3], Phase11,, no. 48, pp , [4],,, vol. 67, no. 4, pp , [5],,, pp. 9 12, [6], 2000,, vol. 61, no. 1, pp , [7] Y. Hiramatsu, T. Aono and M. Nishio: Disaster restoration work for the eruption of Mt Usuzan using an unmanned construction system, Advanced Robotics, vol. 16, no. 6, pp , [8] A. Nishiyama, M. Moteki, K. Fujino and T. Hashimoto: Research on the Comparison of Operator Viewpoints between Manned and Remote Control Operation in Unmanned Construction Systems, Proceeding of the International Symposium on Automation and Robotics in Construction (IS- ARC 2013), pp , [9] M. Kamezaki, J. Yang, H. Iwata and S. Sugano: Visibility Enhancement using Autonomous Multicamera Controls with Situational Role Assignment for Teleoperated Work Machines, Journal of Field Robotics, vol. 33, no. 6, pp , 2016.

28 Horizontal angle correction using straight line detection in an equirectangular image

28 Horizontal angle correction using straight line detection in an equirectangular image 1170283 2017 3 1 2 i Abstract Horizontal angle correction using straight line detection in an equirectangular image