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Parasitic robot system for waypoint navigation of turtle

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Abstract

In research on small mobile robots and biomimetic robots, locomotion ability remains a major issue despite many advances in technology. However, evolution has led to there being many real animals capable of excellent locomotion. This paper presents a “parasitic robot system” whereby locomotion abilities of an animal are applied to a robot task. We chose a turtle as our first host animal and designed a parasitic robot that can perform “operant conditioning”. The parasitic robot, which is attached to the turtle, can induce object-tracking behavior of the turtle toward a Light Emitting Diode (LED) and positively reinforce the behavior through repeated stimulus-response interaction. After training sessions over five weeks, the robot could successfully control the direction of movement of the trained turtles in the waypoint navigation task. This hybrid animal-robot interaction system could provide an alternative solution to some of the limitations of conventional mobile robot systems in various fields, and could also act as a useful interaction system for the behavioral sciences.

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References

  1. Holzer R, Shimoyama I. Locomotion control of a bio-robotic system via electric stimulation. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 1997, 3, 1514–1519.

    Google Scholar 

  2. Talwar S K, Xu S, Hawley E S, Weiss S A, Moxon K A, Chapin J K. Behavioural neuroscience: Rat navigation guided by remote control. Nature, 2002, 417, 37–38.

    Article  Google Scholar 

  3. Pi X, Li S, Xu L, Liu H, Zhou S, Wei K, Wang Z, Zheng X, Wen Z. A preliminary study of the noninvasive remote control system for rat bio-robot. Journal of Bionic Engineering, 2010, 7, 375–381.

    Article  Google Scholar 

  4. Zhang D, Dong Y, Li M, Wang H. A radio-telemetry system for navigation and recording neuronal activity in free-roaming rats. Journal of Bionic Engineering, 2012, 9, 402–410.

    Article  Google Scholar 

  5. Sun C, Zheng N, Zhang X, Chen W, Zheng X. Automatic navigation for rat-robots with modeling of the human guidance. Journal of Bionic Engineering, 2013, 10, 46–56.

    Article  Google Scholar 

  6. Butler Z, Corke P, Peterson R, Rus D. From robots to ani-mals: Virtual fences for controlling cattle. International Journal of Robotics Research, 2006, 25, 485–508.

    Article  Google Scholar 

  7. Harvey C D, Collman F, Dombeck D A, Tank D W. Intra-cellular dynamics of hippocampal place cells during virtual navigation. Nature, 2009, 461, 941–946.

    Article  Google Scholar 

  8. Yu Y, Pan G, Gong Y, Xu K, Zheng N, Hua W, Wu Z. Intel-ligence-augmented rat cyborgs in maze solving. PLOS ONE, 2016, 11, e0147754.

  9. Su L, Zhang N, Yao M, Wu Z. A computational model of the hybrid bio-machine MPMS for ratbots navigation. IEEE Intelligent Systems, 2014, 29, 5–13.

    Article  Google Scholar 

  10. Britt W R, Miller J, Waggoner P, Bevly D M, Hamilton J A. An embedded system for real-time navigation and remote command of a trained canine. Personal and Ubiquitous Computing, 2011, 15, 61–74.

    Article  Google Scholar 

  11. Lee S, Kim C H, Kim D G, Kim H G, Lee P S, Myung H. Remote guidance of untrained turtles by controlling voluntary instinct behavior. PLOS ONE, 2013, 8, e61798.

  12. Kim C H, Choi B J, Kim D G, Lee S, Jo S, Lee P S. Remote navigation of turtle by controlling instinct behavior via human brain-computer interface. Journal of Bionic Engi-neering, 2016, 13, 491–503.

    Article  Google Scholar 

  13. Cai L, Dai Z, Wang W, Wang H, Tang Y. Modulating motor behaviors by electrical stimulation of specific nuclei in pigeons. Journal of Bionic Engineering, 2015, 12, 555–564.

    Article  Google Scholar 

  14. Zhang Y, Sun C, Zheng N, Zhang S, Lin J, Chen W, Zheng X. An automatic control system for ratbot navigation. IEEE/ACM International Conference on Green Computing and Communication & International Conference on Cyber, Physical and Social Computing (CPSCom), 2010, 895–900.

    Google Scholar 

  15. Gao L, Sun C, Zhang C, Zheng N, Chen W, Zheng X. Ratbot automatic navigation by electrical reward stimulation based on distance measurement in unknown environments. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan, 2004, 5315–5318.

    Google Scholar 

  16. Sun C, Zheng N G, Zhang X L, Chen W D, Zheng X X. Automatic navigation for rat-robots with modeling of the human guidance. Journal of Bionic Engineering, 2013, 10, 46–56.

    Article  Google Scholar 

  17. Arnold K, Neumeyer C. Wavelength discrimination in the turtle Pseudemys scripta elegans. Vision Research, 1987, 27, 1501–1511.

    Article  Google Scholar 

  18. Davis K M, Burghardt G M. Training and long-term memory of a novel food acquisition task in a turtle (Pseudemys nel-soni). Behavioural Processes, 2007, 75, 225–230.

    Article  Google Scholar 

  19. Macnab V, Barber I. Some (worms) like it hot: Fish parasites grow faster in warmer water, and alter host thermal preferences. Global Change Biology, 2012, 18, 1540–1548.

    Article  Google Scholar 

  20. Skinner B F. The Behavior of Organisms, Appleton-Century, New York, USA, 1938.

    Google Scholar 

  21. Peterson G B. A day of great illumination: B F Skinner’s discovery of shaping. Journal of the Experimental Analysis of Behavior, 2004, 82, 317–328.

    Article  Google Scholar 

  22. Fossen T I, Breivik M, Skjetne R. Line-of-sight path fol-lowing of underactuated marine craft. Proceedings of the 6th IFAC MCMC, Girona, Spain, 2003.

    Google Scholar 

  23. Norman G, Streiner D L. Biostatistics: The Bare Essentials. B.C Decker Inc, USA, 2001.

    Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-dong, Yuseong-gu, Daejeon, 34141, Republic of Korea

    Dae-Gun Kim, Cheol-Hu Kim & Phill-Seung Lee

  2. Institute for Infocomm Research, 1 Fusionopolis Way, #21-01, Connexis, Singapore

    Serin Lee

  3. Department of Computer Science, Korea Advanced Institute of Science and Technology, (KAIST) 373-1 Guseong-dong, Yuseong-gu, Daejeon, 34141, Republic of Korea

    Sungho Jo

Authors
  1. Dae-Gun Kim
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  2. Serin Lee
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  3. Cheol-Hu Kim
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  4. Sungho Jo
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  5. Phill-Seung Lee
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Correspondence to Phill-Seung Lee.

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Kim, DG., Lee, S., Kim, CH. et al. Parasitic robot system for waypoint navigation of turtle. J Bionic Eng 14, 327–335 (2017). https://doi.org/10.1016/S1672-6529(16)60401-8

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  • DOI: https://doi.org/10.1016/S1672-6529(16)60401-8

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