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Development of Tough Snake Robot Systems

  • Fumitoshi MatsunoEmail author
  • Tetsushi Kamegawa
  • Wei Qi
  • Tatsuya Takemori
  • Motoyasu Tanaka
  • Mizuki Nakajima
  • Kenjiro Tadakuma
  • Masahiro Fujita
  • Yosuke Suzuki
  • Katsutoshi Itoyama
  • Hiroshi G. Okuno
  • Yoshiaki Bando
  • Tomofumi Fujiwara
  • Satoshi Tadokoro
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 128)

Abstract

In the Tough Snake Robot Systems Group, a snake robot without wheels (nonwheeled-type snake robot) and a snake robot with active wheels (wheeled snake robot) have been developed. The main target applications of these snake robots are exploration of complex plant structures, such as the interior and exterior of pipes, debris, and even ladders, and the inspection of narrow spaces within buildings, e.g., roof spaces and underfloor spaces, which would enable plant patrol and inspection. At the head of each robot, a compact and lightweight gripper is mounted to allow the robot to grasp various types of objects, including fragile objects. To measure the contact force of each robot, a whole-body tactile sensor has been developed. A sound-based online localization method for use with the in-pipe snake robot has also been developed. To enable teleoperation of platform robots with the sensing system and the gripper, a human interface has also been developed. The results of some experimental demonstrations of the developed tough snake robot systems are presented.

Notes

Acknowledgements

This work was supported by Impulsing Paradigm Change through Disruptive Technologies (ImPACT) Tough Robotics Challenge program of Japan Science and Technology (JST) Agency.

References

  1. 1.
    Ariizumi, R., Matsuno, F.: Dynamic analysis of three snake robot gaits. IEEE Trans. Robot. 33(5), 1075–1087 (2017)CrossRefGoogle Scholar
  2. 2.
    Baba, T., Kameyama, Y., Kamegawa, T., Gofuku, A.: A snake robot propelling inside of a pipe with helical rolling motion. In: SICE Annual Conference, pp. 2319–2325 (2010)Google Scholar
  3. 3.
    Banconand, G., Huber, B.: Depression and grippers with their possible applications. In: 12th International Symposium for Immunology of Reproduction (ISIR), pp. 321–329 (1982)Google Scholar
  4. 4.
    Bando, Y., Itoyama, K., Konyo, M., Tadokoro, S., Nakadai, K., Yoshii, K., Okuno, H.G.: Microphone-accelerometer based 3D posture estimation for a hose-shaped rescue robot. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5580–5586 (2015).  https://doi.org/10.1109/IROS.2015.7354168
  5. 5.
    Bando, Y., Suhara, H., Tanaka, M., Kamegawa, T., Itoyama, K., Yoshii, K., Matsuno, F., Okuno, H.G.: Sound-based online localization for an in-pipe snake robot. In: 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR2016), pp. 207–213 (2016).  https://doi.org/10.1109/SSRR.2016.7784300
  6. 6.
    Bark, C., Binnenbose, T., Vogele, G., Weisener, T., Widmann, M.: In: In: MEMS 98. IEEE Eleventh Annual International Workshop on Micro Electro Mechanical Systems. An Investigation of Micro Structures, Sensors, Actuators, Machines and Systems, pp. 301–305 (1998)Google Scholar
  7. 7.
    Biagiotti, L., Lotti, F., Melchiorri, C., Vassura, G.: Mechatronic design of innovative fingers for anthropomorphic robot hands. In: 2003 IEEE International Conference on Robotics and Automation (ICRA), pp. 3187–3192(2003)Google Scholar
  8. 8.
    Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269–271 (1959).  https://doi.org/10.1007/BF01386390MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Dollar, A.M., Howe, R.D.: A robust compliant grasper via shape deposition manufacturing. IEEE/ASME Trans. Mech. 11(2), 154–161 (2006)CrossRefGoogle Scholar
  10. 10.
    Dollar, A.M., Howe, R.D.: Simple, : robust autonomous grasping in unstructured environments. In: 2007 IEEE International Conference on Robotics and Automation (ICRA), pp. 4693–4700 (2007)Google Scholar
  11. 11.
    Fujita, T., Shimada, K.: Characteristics and applications of magnetorheological fluids. J.-Magn. Soc. Jpn. 27(3), 91–100 (2003)Google Scholar
  12. 12.
    Fujita, M., Tadakuma, K., Komatsu, H., Takane, E., Nomura, A., Ichimura, T., Konyo, M., Tadokoro, S.: Jamming layered membrane gripper mechanism for grasping differently shaped-objects without excessive pushing force for search and rescue. Adv. Robot. 32(11), 590–604 (2018).  https://doi.org/10.1080/01691864.2018.1451368CrossRefGoogle Scholar
  13. 13.
    Hansen, P., Alismail, H., Rander, P., Browning, B.: Pipe mapping with monocular fisheye imagery. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5180–5185(2013).  https://doi.org/10.1109/IROS.2013.6697105
  14. 14.
    Hasegawa, H., Suzuki, Y., Ming, A., Koyama, K., Ishikawa, M., Shimojo, M.: Net-structure proximity sensor: high-speed and free-form sensor with analog computing circuit. IEEE/ASME Trans. Mech. 20(6), 3232–3241 (2015)CrossRefGoogle Scholar
  15. 15.
    Hayashi, M., Sagisaka, T., Ishizaka, Y., Yoshikai, T., Inaba, M.: Development of functional whole-body flesh with distributed three-axis force sensors to enable close interaction by humanoids. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3610–3615 (2007).  https://doi.org/10.1109/IROS.2007.4399360
  16. 16.
    Hirose, S.: Biologically Inspired Robots: Snake-Like Locomotor and Manipulator. Oxford University Press, Oxford, UK (1987)Google Scholar
  17. 17.
    Hirose, S., Umetani, Y.: Development of soft gripper for the versatile robot hand. Mech. Mach. Theory 13, 351–359 (1978)CrossRefGoogle Scholar
  18. 18.
    Ho, C., Muammer, K.: Design and feasibility tests of a flexible gripper based on inflatable rubber pockets. Int. J. Mach. Tools Manuf. 46(12), 1350–1361 (2006)Google Scholar
  19. 19.
    Ilievski, F., Mazzeo, A.D., Shepherd, R.F., Chen, X., Whitesides, G.M.: Soft robotics for chemists. Angew. Chem. 123(8), 1930–1935 (2011)CrossRefGoogle Scholar
  20. 20.
    ISO: Safety of machinery - Permanent means of access to machinery - Part 3: stairs, stepladders and guard-rails. ISO 14122-3 (2001)Google Scholar
  21. 21.
    Jacoff, A.: Standard test methods for response robots. ASTM International Standards Committee on Homeland Security Applications; Operational Equipment; Robots (E54.08.01) (2016)Google Scholar
  22. 22.
    Kamegawa, T., Yamasaki, T., Igarashi, H., Matsuno, F.: Development of the snake-like rescue robot KOHGA. In: 2004 IEEE International Conference on Robotics and Automation (ICRA), pp. 5081–5086 (2004)Google Scholar
  23. 23.
    Kamegawa, T., Harada, T., Gofuku, A.: Realization of cylinder climbing locomotion with helical form by a snake robot with passive wheels, In: 2009 IEEE International Conference on Robotics and Automation (ICRA), pp. 3067–3072 (2009)Google Scholar
  24. 24.
    Kawasaki, H., Komatsu, T., Uchiyama, K.: Dexterous anthropomorphic robot hand with distributed tactile sensor: Gifu hand II. IEEE/ASME Trans. Mech. 7(3), 296–303 (2002).  https://doi.org/10.1109/TMECH.2002.802720CrossRefGoogle Scholar
  25. 25.
    Kim, D.Y., Kim, J., Kim, I., Jun, S.: Artificial landmark for vision-based SLAM of water pipe rehabilitation robot. In: 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI2015), pp. 444–446 (2015).  https://doi.org/10.1109/URAI.2015.7358900
  26. 26.
    Knapp, C., Carter, G.: The generalized correlation method for estimation of time delay. IEEE Trans. Acoust. Speech Signal Process. 24(4), 320–327 (1976).  https://doi.org/10.1109/TASSP.1976.1162830CrossRefGoogle Scholar
  27. 27.
    Kon, K., Tanaka, M., Tanaka, K.: Mixed integer programming based semi-autonomous step climbing of a snake robot considering sensing strategy. IEEE Trans. Control Syst. Tech. 24(1), 252–264 (2016).  https://doi.org/10.1109/TCST.2015.2429615CrossRefGoogle Scholar
  28. 28.
    Kouno, K., Yamada, H., Hirose, S.: Development of active-joint active-wheel high traversability snake-like robot ACM-R4.2. J. Robot. Mech. 25(3), 559–566 (2013)CrossRefGoogle Scholar
  29. 29.
    Krys, D., Najjaran, H.: Development of visual simultaneous localization and mapping (VSLAM) for a pipe inspection robot. In: 2007 International Symposium on Computational Intelligence in Robotics and Automation (CIRA2007), pp. 344–349 (2007).  https://doi.org/10.1109/CIRA.2007.382850
  30. 30.
    Liljeback, P., Pettersen, K.Y., Stavdahl, O., Gravdahl, J.T.: Snake Robots. Springer, Berlin (2013)CrossRefGoogle Scholar
  31. 31.
    Lim, H., Choi, J.Y., Kwon, Y.S., Jung, E.-J., Yi, B.-J.: SLAM in indoor pipelines with 15mm diameter. In: 2008 IEEE International Conference on Robotics and Automation (ICRA2008), pp. 4005–4011 (2008).  https://doi.org/10.1109/ROBOT.2008.4543826
  32. 32.
    Maruyama, R., Watanabe, T., Uchida, M.: Delicate grasping by robotic gripper with incompressible fluid-based deformable fingertips. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5469–5474(2013)Google Scholar
  33. 33.
    Monkman, G.J., Hesse, S., Steinmann, R., Schunk, H.: Robot Grippers. Wiley, New York (2007)Google Scholar
  34. 34.
    Murphy, R.R.: Disaster Robotics. MIT Press, Cambridge (2014)CrossRefGoogle Scholar
  35. 35.
    Murtra, A.C., Tur, J.M.M.: IMU and cable encoder data fusion for in-pipe mobile robot localization. In: 2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA2013), pp. 1–6 (2013).  https://doi.org/10.1109/TePRA.2013.6556377
  36. 36.
    N\(\acute{u}\tilde{n}\)ez, C.G., Navaraj, W.T., Polat, E.O., Dahiya, R.: Energy-autonomous, flexible, and transparent tactile skin. Adv. Funct. Mater. 27(18) (2017).  https://doi.org/10.1002/adfm.201606287CrossRefGoogle Scholar
  37. 37.
    Ohashi, T., Yamada, H., Hirose, S.: Loop forming snake-like robot ACM-R7 and its serpenoid oval control. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 413–418(2010).  https://doi.org/10.1109/IROS.2010.5651467
  38. 38.
    Okatani, Y., Nishida, T., Tadakuma, K.: Development of universal robot gripper using MR\(\alpha \) fluid. In: 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS), pp. 231–235 (2014)Google Scholar
  39. 39.
    Pettersson, A., Davis, S., Gray, J.O., Dodd, T.J., Ohlsson, T.: Design of a magnetorheological robot gripper for handling of delicate food products with varying shapes. J. Food Eng. 98(3), 332–338 (2010)CrossRefGoogle Scholar
  40. 40.
    Qi, W., Kamegawa, T., Gofuku, A.: Helical wave propagate motion on a vertical pipe with a branch for a snake robot. In: 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM2017), pp. 105–112 (2017)Google Scholar
  41. 41.
    Rollinson, D., Choset, H.: Pipe network locomotion with a snake robot. J. Field Robot. 33(3), 322–336 (2016)CrossRefGoogle Scholar
  42. 42.
    Rollinson, D., Buchan, A., Choset, H.: Virtual chassis for snake robots: definition and applications. Adv. Robot. 26(17), 2043–2064 (2012). http://dblp.uni-trier.de/db/journals/ar/ar26.html#RollinsonBC12CrossRefGoogle Scholar
  43. 43.
    Romano, J.M., Hsiao, K., Niemeyer, G., Chitta, S., Kuchenbecker, K.J.: Human-inspired robotic grasp control with tactile sensing. IEEE Trans. Robot. 27(6), 1067–1079 (2011).  https://doi.org/10.1109/TRO.2011.2162271CrossRefGoogle Scholar
  44. 44.
    Shimojo, M., Araki, T., Teshigawara, S., Ming, A., Ishikawa, M.: A net-structure tactile sensor covering free-form surface and ensuring high-speed response. In: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 670–675 (2007).  https://doi.org/10.1109/IROS.2007.4399084
  45. 45.
    Suzuki, Y.: Multilayered center-of-pressure sensors for robot fingertips and adaptive feedback control. IEEE Robot. Autom. Lett. 2(4), 2180–2187 (2017).  https://doi.org/10.1109/LRA.2017.2723469CrossRefGoogle Scholar
  46. 46.
    Suzuki, Y., Asano, F., Kim, H.-Y., Sone, T.: An optimum computer-generated pulse signal suitable for the measurement of very long impulse responses. J. Acoust. Soc. Am. 97(2), 1119–1123 (1995).  https://doi.org/10.1121/1.412224CrossRefGoogle Scholar
  47. 47.
    Takemori, T., Tanaka, M., Matsuno, F.: Gait design for a snake robot by connecting curve segments and experimental demonstration. IEEE Trans. Robot. PP-99, 1–8 (2018).  https://doi.org/10.1109/TRO.2018.2830346CrossRefGoogle Scholar
  48. 48.
    Takemori, T., Tanaka, M., Matsuno, F.: Ladder climbing with a snake robot. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018)Google Scholar
  49. 49.
    Tanaka, M., Matsuno, F.: Control of snake robots with switching constraints: trajectory tracking with moving obstacle. Adv. Robot. 28(6), 415–419 (2014).  https://doi.org/10.1080/01691864.2013.867285CrossRefGoogle Scholar
  50. 50.
    Tanaka, M., Matsuno, F.: Modeling and control of head raising snake robots by using kinematic redundancy. J. Intell. Robot. Syst. 75(1), 53–69 (2014).  https://doi.org/10.1007/s10846-013-9866-yCrossRefGoogle Scholar
  51. 51.
    Tanaka, M., Tanaka, K.: Control of a snake robot for ascending and descending steps. IEEE Trans. Robot. 31(2), 511–520 (2015).  https://doi.org/10.1109/TRO.2015.2400655CrossRefGoogle Scholar
  52. 52.
    Tanaka, M., Kon, K., Tanaka, K.: Range-sensor-based semiautonomous whole-body collision avoidance of a snake robot. IEEE Trans. Control Syst. Tech. 23(5), 1927–1934 (2015).  https://doi.org/10.1109/TCST.2014.2382578CrossRefGoogle Scholar
  53. 53.
    Tanaka, M., Nakajima, M., Tanaka, K.: Smooth control of an articulated mobile robot with switching constraints. Adv. Robot. 30(1), 29–40 (2016).  https://doi.org/10.1080/01691864.2015.1102646CrossRefGoogle Scholar
  54. 54.
    Tanaka, M., Nakajima, M., Suzuki, Y., Tanaka, K.: Development and control of articulated mobile robot for climbing steep stairs. IEEE/ASME Trans. Mech. 23(2), 531–541 (2018).  https://doi.org/10.1109/TMECH.2018.2792013CrossRefGoogle Scholar
  55. 55.
    Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT Press, Cambridge (2005)Google Scholar
  56. 56.
    Tomo, T.P., Wong, W.K., Schmitz, A., Kristanto, H., Sarazin, A., Jamone, L., Somlor, S., Sugano, S.: A modular, distributed, soft, 3-axis sensor system for robot hands. In: IEEE-RAS 16th International Conference on Humanoid Robots, pp. 454–460(2016).  https://doi.org/10.1109/HUMANOIDS.2016.7803315
  57. 57.
    Transeth, A.A., Leine, R.I., Glocker, C., Pettersen, K.Y.: Snake robot obstacle-aided locomotion: modeling, simulations and experiments. IEEE Trans. Robot. 24(1), 88–104 (2008)CrossRefGoogle Scholar
  58. 58.
    Valenti, R.G., Dryanovski, I., Xiao, J.: Keeping a good attitude: a quaternion-based orientation filter for IMUs and MARGs. Sensors 15(8), 19302–19330 (2015).  https://doi.org/10.3390/s150819302CrossRefGoogle Scholar
  59. 59.
    Vogt, D.M., Park, Y.-L., Wood, R.J.: Design and characterization of a soft multi-axis force sensor using embedded microfluidic channels. IEEE Sens. J. 13(10), 4056–4064 (2013).  https://doi.org/10.1109/JSEN.2013.2272320CrossRefGoogle Scholar
  60. 60.
    Yamada, H., Hirose, S.: Study on the 3D shape of active cord mechanism. In: 2006 IEEE International Conference on Robotics and Automation (ICRA), pp. 2890–2895 (2006).  https://doi.org/10.1109/ROBOT.2006.1642140
  61. 61.
    Yamada, H., Hirose, S.: Study of active cord mechanism –approximations to continuous curves of a multi-joint body. J. Robot. Soc. Jpn. (in Japanese with English summary) 26(1), 110–120 (2008)CrossRefGoogle Scholar
  62. 62.
    Yamada, H., Takaoka, S., Hirose, S.: A snake-like robot for real-world inspection applications (the design and control of a practical active cord mechanism). Adv. Robot. 27(1), 47–60 (2013)CrossRefGoogle Scholar
  63. 63.
    Yamaguchi, A., Atkeson, C.G.: Implementing tactile behaviors using FingerVision. In: IEEE-RAS 17th International Conference on Humanoid Robots, pp. 241–248(2017).  https://doi.org/10.1109/HUMANOIDS.2017.8246881
  64. 64.
    Yatim, N.M., Shauri, R.L.A., Buniyamin, N.: Automated mapping for underground pipelines: an overview. In: 2014 2nd International Conference on Electrical, Electronics and System Engineering (ICEESE2014), pp. 77–82 (2015).  https://doi.org/10.1109/ICEESE.2014.7154599
  65. 65.
    Yim, M., Duff, G.D., Roufas, D.K.: PolyBot: a modular reconfigurable robot. In: 2000 IEEE International Conference on Robotics and Automation (ICRA), pp. 514–520 (2000).  https://doi.org/10.1109/ROBOT.2000.844106
  66. 66.
    Yoshikai, T., Fukushima, H., Hayashi, M., Inaba, M.: Development of soft stretchable knit sensor for humanoids’ whole-body tactile sensibility. In: IEEE-RAS 9th International Conference on Humanoid Robots, pp. 624–631(2009).  https://doi.org/10.1109/ICHR.2009.5379556
  67. 67.
    Yoshikai, T., Tobayashi, K., Inaba, M.: Development of 4-axis soft deformable sensor for humanoid sensor flesh. In: IEEE-RAS 11th International Conference on Humanoid Robots, pp. 205–211 (2011).  https://doi.org/10.1109/Humanoids.2011.6100905
  68. 68.
    Yoshida, K., Muto, T., Kim, J.W., Yokota, S.: An ER microactuator with built-in pump and valve. Int. J. Autom. Technol. (IJAT) 6(4), 468–475 (2012)CrossRefGoogle Scholar
  69. 69.
    Yu, P., Liu, W., Gu, C., Cheng, X., Fu, X.: Flexible piezoelectric tactile sensor array for dynamic three-axis force measurement. Sensors 16(6), (2016).  https://doi.org/10.3390/s16060819CrossRefGoogle Scholar
  70. 70.
    Zhang, C., Florencio, D., Zhang, Z.: Why does PHAT work well in lownoise, reverberative environments? In: 2008 International Conference on Acoustics, Speech, and Signal Processing (ICASSP2008), pp. 2565–2568 (2008).  https://doi.org/10.1109/ICASSP.2008.4518172
  71. 71.
    Zhu, T., Yang, H., Zhang, W.: A Spherical Self-Adaptive Gripper with shrinking of an elastic membrane. In: 2016 International Conference on Advanced Robotics and Mechatronics (ICARM), pp. 512–517 (2016)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Fumitoshi Matsuno
    • 1
    Email author
  • Tetsushi Kamegawa
    • 2
  • Wei Qi
    • 2
  • Tatsuya Takemori
    • 1
  • Motoyasu Tanaka
    • 3
  • Mizuki Nakajima
    • 3
  • Kenjiro Tadakuma
    • 4
  • Masahiro Fujita
    • 4
  • Yosuke Suzuki
    • 5
  • Katsutoshi Itoyama
    • 6
  • Hiroshi G. Okuno
    • 7
  • Yoshiaki Bando
    • 8
  • Tomofumi Fujiwara
    • 1
  • Satoshi Tadokoro
    • 9
  1. 1.Kyoto University, KyodaikatsuraNishikyo-ku, KyotoJapan
  2. 2.Okayama UniversityKita-ku, Okayama-shi, OkayamaJapan
  3. 3.The University of Electro-CommunicationsChofu, TokyoJapan
  4. 4.Tohoku UniversityMiyagiJapan
  5. 5.Kanazawa University, Kakuma-machiKanazawa, IshikawaJapan
  6. 6.Tokyo Institute of TechnologyMeguro-ku, TokyoJapan
  7. 7.Waseda UniversityShinjuku-ku, TokyoJapan
  8. 8.National Institute of Advanced Industrial Science and Technology (AIST)Koto-ku, TokyoJapan
  9. 9.Tohoku UniversityAoba-ku, SendaiJapan

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