Artificial Life and Robotics

, Volume 23, Issue 4, pp 435–443 | Cite as

A dung beetle-inspired robotic model and its distributed sensor-driven control for walking and ball rolling

  • M. ThorEmail author
  • T. Strøm-Hansen
  • L. B. Larsen
  • A. Kovalev
  • S. N. Gorb
  • E. Baird
  • P. Manoonpong
Original Article


A typical approach when designing a bio-inspired robot is to simplify an animal model and to enhance the functionality of interest. For hexapod robots, this often leads to a need of supplementary mechanics to become multifunctional. However, a preferable solution is to employ the embodied multifunctional capabilities of the animal as inspiration for robot design. Using this approach, we present a method for translating the kinematic chain of a dung beetle from which an accurate kinematic model and a simplified one were simulated and compared. The beetle was selected due to its multifunctional locomotory capabilities including walking as well as standing on and rolling a ball. For testing the models, we developed a distributed sensor-driven controller that can generate walking and ball-rolling behaviors. A comparison of the two modeling approaches shows a similar performance with regards to walking stability and accuracy, but differences when it comes to speed and multifunctionality. This is because the accurate model is able to use its legs to walk faster and roll a ball, which the simplified one is not. In conclusion, the accurate model of a dung beetle-inspired robot is advantageous as it, together with our novel control mechanism, is able to elicit behaviors comparable to those of the real dung beetle (i.e., walking and rolling a dung ball).


Bio-inspired robotics Embodied AI Hexapod locomotion Object manipulation 



This work was supported by the Human Frontier Science Program under grant agreement no. RGP0002/2017 and Center for BioRobotics (CBR) at University of Southern Denmark (SDU, Denmark). We express a deep sense of gratitude to John Hallam for his comments and proofreading.


  1. 1.
    Webb B (2002) Robots in invertebrate neuroscience. Nature 417:359–363CrossRefGoogle Scholar
  2. 2.
    Karakasiliotis K, Thandiackal R, Melo K, Horvat T, Mahabadi NK, Tsitkov S, Cabelguen JM, Ijspeert AJ (2016) From cineradiography to biorobots: an approach for designing robots to emulate and study animal locomotion. J R Soc Interface 13(119):1–15CrossRefGoogle Scholar
  3. 3.
    Abbott A (2007) Biological robotics: working out the bugs. Nature 445:250–253CrossRefGoogle Scholar
  4. 4.
    Schneider A, Paskarbeit J, Schilling M, Schmitz J (2014) HECTOR, a bio-inspired and compliant hexapod robot. In: Proceedings of the 3rd conference on biomimetics and biohybrid systems. Living Mach 2014, pp 427–430Google Scholar
  5. 5.
    Johnson JJS (2017) Dung beetles: promoters of prairie preservation. Acts Facts. Institute for Creation Research. Accessed 14 July 2018
  6. 6.
    Smolka J, Baird E, Byrne MJ, El Jundi B, Warrant EJ, Dacke M (2012) Dung beetles use their dung ball as a mobile thermal refuge. Curr Biol 22(20):863–864CrossRefGoogle Scholar
  7. 7.
    Goel AK, McAdams DA, Stone RB (2014) Biologically inspired design. Springer, LondonCrossRefGoogle Scholar
  8. 8.
    Manoonpong P, Parlitz U, Wörgötter F (2013) Neural control and adaptive neural forward models for insect-like, energy efficient, and adaptable locomotion of walking machines. Front Neural Circ 7(12):1–28Google Scholar
  9. 9.
    Heppner G, Buettner T, Roennau A, Dillmann R (2014) Versatile—high power gripper for a six legged walking robot. Mobile Serv Robot. CrossRefGoogle Scholar
  10. 10.
    Philips TK, Pretorius E, Scholtz CH (2004) A phylogenetic analysis of the dung beetles: (Scarabaeinae: Scarabaeidæ): Unrolling an evolutionary history. Invertebr Syst 18:1–36CrossRefGoogle Scholar
  11. 11.
    Halffter G, Matthews E (1966) The natural history of dung beetles of the subfamily scarabaeidae. Fol Entomol Mex 12–14:1–312Google Scholar
  12. 12.
    Cruse H, Kindermann T, Schumm M, Dean J, Schmitz J (1998) Walknet—a biologically inspired network to control six-legged walking. Neural Netw 11(7–8):1435–1447CrossRefGoogle Scholar
  13. 13.
    Beynon SA (2008) Geotrupes stercorarius top/bottom view picture, all about beetles. Accessed 17 May 2016
  14. 14.
    Di Canio G, Stoyanov S, Larsen JC, Hallam J, Kovalev A, Kleinteich T, Gorb SN, Manoonpong P (2016) A robot leg with compliant tarsus and its neural control for efficient and adaptive locomotion on complex terrains. Artif Life Robot 21:274–281CrossRefGoogle Scholar
  15. 15.
    Hesse F, Martius G, Manoonpong P, Biehl M, Wörgötter F (2012) Modular robot control environment-testing neural control on simulated and real robots. In: Front Comput Neurosci, Conference abstract: bernstein conference (Munich), pp 1416–1420Google Scholar
  16. 16.
    Gladun F, Gorb SN (2007) Insect walking techniques on thin stems. Arthropod-Plant Interact 1(2):77–91CrossRefGoogle Scholar
  17. 17.
    Schilling M, Hoinville T, Schmitz J, Cruse H (2013) Walknet, a bio-inspired controller for hexapod walking. Biol Cybern 107(4):397–419MathSciNetCrossRefGoogle Scholar
  18. 18.
    Brooks R (1990) Elephants dont play chess. Robot Auton Syst 6(1–2):3–15CrossRefGoogle Scholar
  19. 19.
    Sørensen CTL, Manoonpong P (2016) Modular neural control for object transportation of a bio-inspired hexapod robot. simulation of adaptive behavior (SAB). LNCS 9825:67–78Google Scholar
  20. 20.
    Di Canio G, Stoyanov S, Balmori IT, Larsen JC, Manoonpong P (2016) Adaptive combinatorial neural control for robust locomotion of a biped robot. simulation of adaptive behavior (SAB). LNCS 9825:317–328Google Scholar

Copyright information

© ISAROB 2018

Authors and Affiliations

  • M. Thor
    • 1
    Email author
  • T. Strøm-Hansen
    • 1
  • L. B. Larsen
    • 1
  • A. Kovalev
    • 2
  • S. N. Gorb
    • 2
  • E. Baird
    • 3
  • P. Manoonpong
    • 1
    • 4
  1. 1.Embodied AI and Neurorobotics Lab, Centre for BioRobotics, The Mæsk Mc-Kinney Møller InstituteThe University of Southern DenmarkOdenseDenmark
  2. 2.Functional Morphology and Biomechanics, Zoological InstituteKiel UniversityKielGermany
  3. 3.Department of BiologyLund UniversityLundSweden
  4. 4.Bio-inspired Robotics and Neural Engineering Lab, School of Information Science and TechnologyVidyasirimedhi Institute of Science and TechnologyRayongThailand

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