Skip to main content
Log in

How a serpentine tail assists agile motions of kangaroo rats: a dynamics and control approach

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

Kangaroo rat is a good representative for general bipedalism with a serpentine tail. Modeling and analyzing the kangaroo rat motion helps to understand the serpentine tail functionalities in agile motions of bipedal mobile platforms, and this understanding is expected to lay the foundation for the future development of such robotic systems. This paper analyzes the kangaroo rat motions through dynamic modeling and control. The system dynamic model is established using the inertia matrix method, and two typical serpentine tail models are considered: a continuum tail model where the tail is modeled as several constant curvature arcs, and an articulated tail model where the tail is discretized into rigid links. Regularized contact model is used to compute the ground reaction force (GRF). To automatically plan the tail motion, numerical optimal control techniques (i.e., direct collocation method) are utilized. Partial feedback linearization is then used to track the designed tail trajectory. Based on the formulated dynamic model and motion controller, two representative tail functions (airborne righting and supporting) were simulated and analyzed. The results validated the proposed modeling and control framework and showed the nontrivial functionalities of the serpentine tail in helping the kangaroo rat to achieve agile motions. Moreover, comparative studies on the two tail models and the tail segmentations were performed to analyze the model differences. The results demonstrated that the articulated tail model is a good approximation of the continuum tail model, and more tail segments and links enhance the kangaroo rat’s ability to deliberately adjust its motion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Code availability

Custom code.

References

  1. Hickman, G.C.: The mammalian tail: a review of functions. Mammal Rev. 9(4), 143–157 (1979)

    Article  MathSciNet  Google Scholar 

  2. Schwaner, M.J., Hsieh, S.T., Braasch, I., Bradley, S., Campos, C.B., Collins, C.E., Donatelli, C.M., Fish, F.E., Fitch, O.E., Flammang, B.E., Jackson, B.E.: Future tail tales: a forward-looking, integrative perspective on tail research. Integr. Comp. Biol. 61(2), 521–537 (2021)

    Article  Google Scholar 

  3. Young, J.W., Chadwell, B.A., Dunham, N.T., McNamara, A., Phelps, T., Hieronymus, T., Shapiro, L.J.: The stabilizing function of the tail during arboreal quadrupedalism. Integr. Comp. Biol. 61(2), 491–505 (2021)

    Article  Google Scholar 

  4. Dawson, R.S., Warburton, N.M., Richards, H.L., Milne, N.: Walking on five legs: investigating tail use during slow gait in kangaroos and wallabies. Aust. J. Zool. 63(3), 192–200 (2015)

    Article  Google Scholar 

  5. Zeglin, G.J.: Uniroo—a one legged dynamic hopping robot. Bachelor thesis, Massachusetts Institute of Technology, Cambridge, MA, USA (1991)

  6. Libby, T., Moore, T.Y., Chang-Siu, E., Li, D., Cohen, D.J., Jusufi, A., Full, R.J.: Tail-assisted pitch control in lizards, robots and dinosaurs. Nature 481(7380), 181–184 (2012)

    Article  Google Scholar 

  7. Jusufi, A., Kawano, D.T., Libby, T., Full, R.J.: Righting and turning in mid-air using appendage inertia: reptile tails, analytical models and bio-inspired robots. Bioinspir. Biomim. 5(4), 045001 (2010)

    Article  Google Scholar 

  8. Chang-Siu, E., Libby, T., Brown, M., Full, R.J., Tomizuka, M.: A nonlinear feedback controller for aerial self-righting by a tailed robot. In: Proceedings of the IEEE International Conference on Robotics and Automation, Karlsruhe, Germany (2013)

  9. Libby, T., Johnson, A.M., Chang-Siu, E., Full, R.J., Koditschek, D.E.: Comparative design, scaling, and control of appendages for inertial reorientation. IEEE Trans. Rob. 32(6), 1380–1398 (2016)

    Article  Google Scholar 

  10. De, A., Koditschek, D.E.: Parallel composition of templates for tail-energized planar hopping. In: Proceedings of the IEEE International Conference on Robotics and Automation, Seattle, USA (2015).

  11. Casarez, C.S., Fearing, R.S.: Steering of an underactuated legged robot through terrain contact with an active tail. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Madrid, Spain (2018)

  12. Kohut, N.J., Pullin, A.O., Haldane, D.W., Zarrouk, D., Fearing, R.S.: Precise dynamic turning of a 10 cm legged robot on a low friction surface using a tail. In: Proceedings of the IEEE International Conference on Robotics and Automation, Karlsruhe, Germany (2013).

  13. Patel, A., Boje, E.: On the conical motion of a two-degree-of-freedom tail inspired by the cheetah. IEEE Trans. Rob. 31(6), 1555–1560 (2015)

    Article  Google Scholar 

  14. Norby, J., Li, J.Y., Selby, C., Patel, A., Johnson, A.M.: Enabling dynamic behaviors with aerodynamic drag in lightweight tails. IEEE Trans. Robot. (2021). https://doi.org/10.1109/TRO.2020.3045644

    Article  Google Scholar 

  15. Zhao, J., Zhao, T., Xi, N., Mutka, M.W., Xiao, L.: Msu tailbot: controlling aerial maneuver of a miniature-tailed jumping robot. IEEE/ASME Trans. Mechatron. 20(6), 2903–2914 (2015)

    Article  Google Scholar 

  16. Liu, G.H., Lin, H.Y., Lin, H.Y., Chen, S.T., Lin, P.C.: A bio-inspired hopping kangaroo robot with an active tail. J. Bionic Eng. 11(4), 541–555 (2014)

    Article  Google Scholar 

  17. Briggs, R., Lee, J., Haberland, M., Kim, S.: Tails in biomimetic design: analysis, simulation, and experiment. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Portugal (2012)

  18. Heim, S.W., Ajallooeian, M., Eckert, P., Vespignani, M., Ijspeert, A.J.: On designing an active tail for legged robots: simplifying control via decoupling of control objectives. Indus. Robot Int. J. 43(3), 338–346 (2016)

    Article  Google Scholar 

  19. Ikeda, F., Toyama, S.: A proposal of right and left turning mechanism for quasi-passive walking robot. In: Proceedings of the International Conference on Advanced Robotics and Intelligent Systems, Taipei, Taiwan (2015)

  20. Machairas, K., Papadopoulos, E.: On quadruped attitude dynamics and control using reaction wheels and tails. In: Proceedings of the European Control Conference, Linz, Austria (2015)

  21. Rone, W.S., Saab, W., Ben-Tzvi, P.: Design, modeling, and integration of a flexible universal spatial robotic tail. J. Mech. Robot. 10(4), 041001 (2018)

    Article  Google Scholar 

  22. Liu, Y., Wang, J., Ben-Tzvi, P.: A cable length invariant robotic tail using a circular shape universal joint mechanism. J. Mech. Robot. 11(5), 051005 (2019)

    Article  Google Scholar 

  23. Saab, W., Rone, W., Kumar, A., Ben-Tzvi, P.: Design and integration of a novel spatial articulated robotic tail. IEEE/ASME Trans. Mechatron. 24(2), 434–446 (2019)

    Article  Google Scholar 

  24. Liu, Y., Ben-Tzvi, P.: Design, analysis, and integration of a new two-degree-of-freedom articulated multi-link robotic tail mechanism. J. Mech. Robot. 12(2), 021101 (2020)

    Article  Google Scholar 

  25. Santiago, J.L.C., Godage, I.S., Gonthina, P., Walker, I.D.: Soft robots and kangaroo tails: modulating compliance in continuum structures through mechanical layer jamming. Soft Rob. 3(2), 54–63 (2016)

    Article  Google Scholar 

  26. Simon, B., Sato, R., Choley, J.Y., Ming, A.: Development of a bio-inspired flexible tail systemxs. In: Proceedings of the 12th France-Japan and 10th Europe-Asia Congress on Mechatronics, Tsu (2018)

  27. Nabeshima, J., Saraiji, M.Y., Minamizawa, K.: Prosthetic Tail: Artificial Anthropomorphic Tail for Extending Innate Body Functions. In: Proceedings of the 10th Augmented Human International Conference, Reims (2019)

  28. Rone, W.S., Saab, W., Kumar, A., Ben-Tzvi, P.: Controller design, analysis, and experimental validation of a robotic serpentine tail to maneuver and stabilize a quadrupedal robot. J. Dyn. Syst. Meas. Contr. 141(8), 081002 (2019)

    Article  Google Scholar 

  29. Kangaroo rat mid-air maneuver via tail rotation. Ninja Rat, https://www.youtube.com/watch?v=aV8_iv6SXqc, Retrieved 2021

  30. Freymiller, G.A., Whitford, M.D., Higham, T.E., Clark, R.W.: Escape dynamics of free-ranging desert kangaroo rats (Rodentia: Heteromyidae) evading rattlesnake strikes. Biol. J. Lin. Soc. 127(1), 164–172 (2019)

    Article  Google Scholar 

  31. Schwaner, M.J., Freymiller, G.A., Clark, R.W., McGowan, C.P.: How to stick the landing: kangaroo rats use their tails to reorient during evasive jumps away from predators. Integr. Comp. Biol. 61(2), 442–454 (2021)

    Article  Google Scholar 

  32. Moore, J., Gutmann, A., Craig, M., McKinley, P.: Exploring the role of the tail in bipedal hopping through computational evolution. Artif. Life 25(3), 236–249 (2019)

    Article  Google Scholar 

  33. An, J., Chung, T.Y., Lo, C.H.D., Ma, C., Chu, X., Au, K.S.: Development of a bipedal hopping robot with morphable inertial tail for agile locomotion. In: Proceedings of the 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, New York (2020)

  34. Featherstone, R.: Rigid body dynamics algorithms. Springer, Berlin (2014)

    MATH  Google Scholar 

  35. Liu, Y., Ben-Tzvi, P.: Dynamic modeling, analysis, and comparative study of a quadruped with bio-inspired robotic tails. Multibody Sys. Dyn. 51(2), 195–219 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  36. Godage, I.S., Webster, R.J., Walker, I.D.: Center-of-gravity-based approach for modeling dynamics of multisection continuum arms. IEEE Trans. Rob. 35(5), 1097–1108 (2019)

    Article  Google Scholar 

  37. Chirikjian, G.S.: Hyper-redundant manipulator dynamics: a continuum approximation. Adv. Robot. 9(3), 217–243 (1994)

    Article  Google Scholar 

  38. Liu, Y., Ben-Tzvi, P.: A new approach to model constant curvature continuum robot dynamics. In: Proceedings of the ASME 2019 Dynamic Systems and Control Conference, Park City, Utah (2019)

  39. Azad, M., Featherstone, R.: A new nonlinear model of contact normal force. IEEE Trans. Rob. 30(3), 736–739 (2014)

    Article  Google Scholar 

  40. Flores, P.: Contact mechanics for dynamical systems: a comprehensive review. Multibody Syst. Dyn. (2021). https://doi.org/10.1007/s11044-021-09803-y

    Article  Google Scholar 

  41. Rao, A.V.: A survey of numerical methods for optimal control. Adv. Astronaut. Sci. 135(1), 497–528 (2009)

    Google Scholar 

  42. Tassa, Y., Mansard, N., Todorov, E.: Control-limited differential dynamic programming. In: Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong (2014)

  43. Kelly, M.: An introduction to trajectory optimization: how to do your own direct collocation. SIAM Rev. 59(4), 849–904 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  44. Garg, D., Patterson, M., Hager, W.W., Rao, A.V., Benson, D.A., Huntington, G.T.: A unified framework for the numerical solution of optimal control problems using pseudospectral methods. Automatica 46(11), 1843–1851 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  45. Liu, Y., Ben-Tzvi, P.: Dynamic modeling, analysis, and design synthesis of a reduced complexity quadruped with a serpentine robotic tail. Integr. Comp. Biol. 61(2), 464–477 (2021)

    Article  Google Scholar 

  46. Bryson, A.E., Ho, Y.C.: Applied optimal control: optimization, estimation, and control. Taylor & Francis Group, New York (1975)

    Google Scholar 

  47. Betts, J.T.: Practical methods for optimal control and estimation using nonlinear programming, 2nd edn. Society for Industrial and Applied Mathematics, Philadelphia (2010)

    Book  MATH  Google Scholar 

  48. Kuindersma, S., Deits, R., Fallon, M., Valenzuela, A., Dai, H., Permenter, F., Koolen, T., Marion, P., Tedrake, R.: Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot. Auton. Robot. 40(3), 429–455 (2016)

    Article  Google Scholar 

  49. Mordatch, I., Todorov, E., Popović, Z.: Discovery of complex behaviors through contact-invariant optimization. ACM Trans. Graph. 31(4), 1–8 (2012)

    Article  Google Scholar 

  50. Posa, M., Cantu, C., Tedrake, R.: A direct method for trajectory optimization of rigid bodies through contact. Int. J. Robot. Res. 33(1), 69–81 (2014)

    Article  Google Scholar 

  51. Mastalli, C., Budhiraja, R., Merkt, W., Saurel, G., Hammoud, B., Naveau, M., Carpentier, J., Righetti, L., Vijayakumar, S., Mansard, N.: Crocoddyl: An efficient and versatile framework for multi-contact optimal control. In: Proceedings of the IEEE International Conference on Robotics and Automation, Paris (2020)

  52. Chatzinikolaidis, I., Li, Z.: Trajectory optimization of contact-rich motions using implicit differential dynamic programming. IEEE Robot. Automat. Lett. 6(2), 2626–2633 (2021)

    Article  Google Scholar 

  53. Carpentier, J., Mansard, N.: Analytical derivatives of rigid body dynamics algorithms. In: Proceedings of the Robotics: Science and Systems, Pittsburgh, Pennsylvania (2018)

  54. Boyd, S., Vandenberghe, L.: Convex optimization. Cambridge University Press, New York (2004)

    Book  MATH  Google Scholar 

Download references

Acknowledgements

This material is based upon work supported by (while serving at) the National Science Foundation under Grant No. 1906727.

Funding

This work was supported by the National Science Foundation under Grant No. 1906727.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pinhas Ben-Tzvi.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

To better illustrate the numerical results in the manuscript, we have created a video containing the animations of the simulations in Section 4. This video (in mp4 format) can be found both in the “Electronic Supplementary Material” item type and online at https://youtu.be/wy067QQ0Cvs.

Appendices

Appendix A: Articulated tail kinematics

The velocities, Jacobians, acceleration, and MOI for each link of the articulated tail model are computed recursively using Eqs. (A1A13). Eq. (A14) computes the torso MOI. \({\mathbf{u}}_{x,y}\) is an x-dimension unit column vector with 1 on the y-th entry.

$$ {{\varvec{\upomega}}}_{j} = \left\{ {\begin{array}{*{20}l} {{{\varvec{\upomega}}}_{b} , j = 0} \\ {{{\varvec{\upomega}}}_{j - 1} + \dot{\alpha }_{i} {\mathbf{x}}_{j - 1} + \dot{\beta }_{i} {\mathbf{z}}_{j} , j > 0} \\ \end{array} } \right. $$
(A1)
$$ {\mathbf{v}}_{j,com} = {\mathbf{v}}_{j,jnt} + {\mathbf{v}}_{j,j2c} $$
(A2)
$$ {\mathbf{v}}_{j,jnt} = \left\{ {\begin{array}{*{20}l} {{\mathbf{v}}_{b} + {{\varvec{\upomega}}}_{b} \times {\mathbf{p}}_{b2t} , j = 1} \\ {{\mathbf{v}}_{j - 1,jnt} + {\mathbf{v}}_{j - 1,j2j} , j > 1} \\ \end{array} } \right. $$
(A3)
$$ \left\{ {\begin{array}{*{20}c} {{\mathbf{v}}_{j,j2c} = {{\varvec{\upomega}}}_{j} \times {\mathbf{p}}_{j,j2c} } \\ {{\mathbf{v}}_{j,j2j} = {{\varvec{\upomega}}}_{j} \times {\mathbf{p}}_{j,j2j} } \\ \end{array} } \right. $$
(A4)
$$ {\mathbf{J}}_{j,\omega } = \left\{ {\begin{array}{*{20}l} {\left[ {\begin{array}{*{20}c} {0_{3 \times 3} } & {{\mathbf{I}}_{3 \times 3} } & {0_{3 \times 2m} } \\ \end{array} } \right], j = 0} \\ {{\mathbf{J}}_{j - 1,\omega } + {\mathbf{x}}_{j - 1} {\mathbf{u}}_{d,2i + 5}^{T} + {\mathbf{z}}_{j} {\mathbf{u}}_{d,2i + 6}^{T} , j > 0} \\ \end{array} } \right. $$
(A5)
$$ {\mathbf{J}}_{j,com} = {\mathbf{J}}_{j,jnt} + {\mathbf{J}}_{j,j2c} $$
(A6)
$$ {\mathbf{J}}_{j,jnt} = \left\{ {\begin{array}{*{20}l} {\left[ {\begin{array}{*{20}c} {{\mathbf{I}}_{3 \times 3} } & { - {\tilde{\mathbf{p}}}_{b2t} } & {0_{3 \times 2m} } \\ \end{array} } \right], j = 1} \\ {{\mathbf{J}}_{j - 1,jnt} + {\mathbf{J}}_{j - 1,j2j} , j > 1} \\ \end{array} } \right. $$
(A7)
$$ \left\{ {\begin{array}{*{20}c} {{\mathbf{J}}_{j,j2c} = - {\tilde{\mathbf{p}}}_{j,j2c} {\mathbf{J}}_{j,\omega } } \\ {{\mathbf{J}}_{j,j2j} = - {\tilde{\mathbf{p}}}_{j,j2j} {\mathbf{J}}_{j,\omega } } \\ \end{array} } \right. $$
(A8)
$$ {\dot{\mathbf{\omega }}}_{j} = \left\{ {\begin{array}{*{20}l} {{\dot{\mathbf{\omega }}}_{b} , j = 0} \\ {{\dot{\mathbf{\omega }}}_{j - 1} + \ddot{\alpha }_{i} {\mathbf{x}}_{j - 1} } \\ { + \dot{\alpha }_{i} {\tilde{\mathbf{\omega }}}_{j - 1} {\mathbf{x}}_{j - 1} + \ddot{\beta }_{i} {\mathbf{z}}_{j} + \dot{\beta }_{i} {\tilde{\mathbf{\omega }}}_{j} {\mathbf{z}}_{j} , j > 0} \\ \end{array} } \right. $$
(A9)
$$ {\dot{\mathbf{v}}}_{j,com} = {\dot{\mathbf{v}}}_{j,jnt} + {\dot{\mathbf{v}}}_{j,j2c} $$
(A10)
$$ {\dot{\mathbf{v}}}_{j,jnt} = \left\{ {\begin{array}{*{20}l} {{\dot{\mathbf{v}}}_{b} + \widetilde{{{\dot{\mathbf{\omega }}}}}_{b} {\mathbf{p}}_{b2t} + {\tilde{\mathbf{\omega }}}_{b}^{2} {\mathbf{p}}_{b2t} , j = 1} \\ {{\dot{\mathbf{v}}}_{j - 1,jnt} + {\dot{\mathbf{v}}}_{j - 1,j2j} , j > 1} \\ \end{array} } \right. $$
(A11)
$$ \left\{ {\begin{array}{*{20}c} {{\dot{\mathbf{v}}}_{j,j2c} = \widetilde{{{\dot{\mathbf{\omega }}}}}_{j} {\mathbf{p}}_{j,j2c} + {\tilde{\mathbf{\omega }}}_{j}^{2} {\mathbf{p}}_{j,j2c} } \\ {{\dot{\mathbf{v}}}_{j,j2j} = \widetilde{{{\dot{\mathbf{\omega }}}}}_{j} {\mathbf{p}}_{j,j2j} + {\tilde{\mathbf{\omega }}}_{j}^{2} {\mathbf{p}}_{j,j2j} } \\ \end{array} } \right. $$
(A12)
$$ {\mathbf{I}}_{j,at} = {\mathbf{R}}_{j}\,\,^{j} {\mathbf{I}}_{j,at} {\mathbf{R}}_{j}^{T} $$
(A13)
$$ {\mathbf{I}}_{b} = {\mathbf{R}}_{b} {}_{ }^{b} {\mathbf{I}}_{b} {\mathbf{R}}_{b}^{T} $$
(A14)

Appendix B: Continuum tail kinematics

The detailed expression of matrix \({\mathbf{E}}_{i,v}\) is given as follows where \({\mathrm{c}}_{\theta }=\mathrm{cos}{\theta }_{i}\), \({\mathrm{s}}_{\theta }=\mathrm{sin}{\theta }_{i}\), \({\mathrm{c}}_{2\theta }=\mathrm{cos}2{\theta }_{i}\), \({\mathrm{s}}_{2\theta }=\mathrm{sin}2{\theta }_{i}\). Since \({\mathbf{E}}_{i,v}\) is symmetric, only the upper triangle elements are listed.

$${\mathbf{E}}_{i,v}\left(\mathrm{1,1}\right)=1$$
$${\mathbf{E}}_{i,v}\left(\mathrm{1,2}\right)=(1-{\mathrm{c}}_{\theta })/{\theta }_{i}$$
$${\mathbf{E}}_{i,v}\left(\mathrm{1,3}\right)=(-1+{\mathrm{c}}_{\theta }+{\theta }_{i}{\mathrm{s}}_{\theta })/{\theta }_{i}^{2}$$
$${\mathbf{E}}_{i,v}\left(\mathrm{1,4}\right)=-{\mathrm{s}}_{\theta }/{\theta }_{i}$$
$${\mathbf{E}}_{i,v}\left(\mathrm{1,5}\right)=(-{\theta }_{i}{\mathrm{c}}_{\theta }+{\mathrm{s}}_{\theta })/{\theta }_{i}^{2}$$
$${\mathbf{E}}_{i,v}\left(\mathrm{2,2}\right)=1/2-{\mathrm{s}}_{2\theta }/(4{\theta }_{i})$$
$${\mathbf{E}}_{i,v}\left(\mathrm{2,3}\right)=(-2{\theta }_{i}{\mathrm{c}}_{2\theta }+{\mathrm{s}}_{2\theta })/(8{\theta }_{i}^{2})$$
$${\mathbf{E}}_{i,v}\left(\mathrm{2,4}\right)=({\mathrm{c}}_{2\theta }-1)/(4{\theta }_{i})$$
$${\mathbf{E}}_{i,v}\left(\mathrm{2,5}\right)=(1-{\mathrm{c}}_{2\theta }-2{\theta }_{i}{\mathrm{s}}_{2\theta }+2{\theta }_{i}^{2})/(8{\theta }_{i}^{2})$$
$${\mathbf{E}}_{i,v}\left(\mathrm{3,3}\right)=(4{\theta }_{i}^{3}+6{\theta }_{i}{\mathrm{c}}_{2\theta }+(6{\theta }_{i}^{2}-3){\mathrm{s}}_{2\theta })/(24{\theta }_{i}^{3})$$
$${\mathbf{E}}_{i,v}\left(\mathrm{3,4}\right)={\mathbf{E}}_{i,v}\left(\mathrm{2,5}\right)-1/2$$
$${\mathbf{E}}_{i,v}\left(\mathrm{3,5}\right)=(-1+(1-2{\theta }_{i}^{2}){\mathrm{c}}_{2\theta }+2{\theta }_{i}{\mathrm{s}}_{2\theta })/(8{\theta }_{i}^{3})$$
$${\mathbf{E}}_{i,v}\left(\mathrm{4,4}\right)=1-{\mathbf{E}}_{i,v}\left(\mathrm{2,2}\right)$$
$${\mathbf{E}}_{i,v}\left(\mathrm{4,5}\right)=-{\mathbf{E}}_{i,v}\left(\mathrm{2,3}\right)$$
$${\mathbf{E}}_{i,v}\left(\mathrm{5,5}\right)=(4{\theta }_{i}^{3}-6{\theta }_{i}{\mathrm{c}}_{2\theta }+(3-6{\theta }_{i}^{2}){\mathrm{s}}_{2\theta })/(24{\theta }_{i}^{3})$$

The elements in matrix \({\mathbf{Q}}_{i,v}\) are given as:

$${\mathbf{Q}}_{i,v}\left(\mathrm{1,1}\right)=1$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{2,1}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{1,2}\right)=(1-{\mathrm{c}}_{\theta })/{\theta }_{i}$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{3,1}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{1,4}\right)=(-1+{\mathrm{c}}_{\theta }+{\theta }_{i}{\mathrm{s}}_{\theta })/{\theta }_{i}^{2}$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{4,1}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{1,6}\right)=-{\mathrm{s}}_{\theta }/{\theta }_{i}$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{5,1}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{1,8}\right)=(-{\theta }_{i}{\mathrm{c}}_{\theta }+{\mathrm{s}}_{\theta })/{\theta }_{i}^{2}$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{2,2}\right)=1-{\mathbf{Q}}_{i,v}\left(\mathrm{4,6}\right)=1/2-{\mathrm{s}}_{2\theta }/(4{\theta }_{i})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{3,2}\right)=(-2{\theta }_{i}{\mathrm{c}}_{2\theta }+{\mathrm{s}}_{2\theta })/(8{\theta }_{i}^{2})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{3,2}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{2,4}\right)=-{\mathbf{Q}}_{i,v}\left(\mathrm{5,6}\right)=-{\mathbf{Q}}_{i,v}\left(\mathrm{4,8}\right)$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{4,2}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{2,6}\right)=({\mathrm{c}}_{2\theta }-1)/(4{\theta }_{i})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{5,2}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{2,8}\right)=(1-{\mathrm{c}}_{2\theta }-2{\theta }_{i}{\mathrm{s}}_{2\theta }+2{\theta }_{i}^{2})/(8{\theta }_{i}^{2})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{3,4}\right)=(4{\theta }_{i}^{3}+6{\theta }_{i}{\mathrm{c}}_{2\theta }+(6{\theta }_{i}^{2}-3){\mathrm{s}}_{2\theta })/(24{\theta }_{i}^{3})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{3,4}\right)=-{\mathbf{Q}}_{i,v}\left(\mathrm{4,9}\right)$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{4,4}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{3,6}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{5,2}\right)-1/2$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{5,4}\right)=(-1+(1-2{\theta }_{i}^{2}){\mathrm{c}}_{2\theta }+2{\theta }_{i}{\mathrm{s}}_{2\theta })/(8{\theta }_{i}^{3})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{5,4}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{4,5}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{3,8}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{2,9}\right)$$
$${\mathbf{Q}}_{i,v}\left(:,3\right)=2{\mathbf{Q}}_{i,v}\left(:,4\right)$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{1,5}\right)=(2+\left({\theta }_{i}^{2}-2\right){\mathrm{c}}_{\theta }-2{\theta }_{i}{\mathrm{s}}_{\theta })/{\theta }_{i}^{3}$$
$${\mathbf{Q}}_{i,v}\left(2,5\right)=-{\mathbf{Q}}_{i,v}\left(\mathrm{5,8}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{3,4}\right)-1/3$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{3,5}\right)=(2{\theta }_{i}(2{\theta }_{i}^{2}-3){\mathrm{c}}_{2\theta }-(6{\theta }_{i}^{2}-3){\mathrm{s}}_{2\theta })/(16{\theta }_{i}^{4})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{3,5}\right)=-{\mathbf{Q}}_{i,v}\left(\mathrm{5,9}\right)$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{5,5}\right)=(3+2{\theta }_{i}\left(2{\theta }_{i}^{2}-3\right){\mathrm{s}}_{2\theta }+(6{\theta }_{i}^{2}-3){\mathrm{c}}_{2\theta }-2{\theta }_{i}^{4})/(16{\theta }_{i}^{4})$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{5,5}\right)={\mathbf{Q}}_{i,v}\left(\mathrm{3,9}\right)-1/4$$
$${\mathbf{Q}}_{i,v}\left(:,7\right)=2{\mathbf{Q}}_{i,v}\left(:,8\right)$$
$${\mathbf{Q}}_{i,v}\left(\mathrm{1,9}\right)=(\left({\theta }_{i}^{2}-2\right){\mathrm{s}}_{\theta }+2{\theta }_{i}{\mathrm{c}}_{\theta })/{\theta }_{i}^{3}$$

The block-wise matrix multiplication notation “\(\circ \)” is introduced in Sect. 2.3 to express the sum of scalar multiplications (linear combination of vectors). To better present its operations, an example is given here.

$$\mathbf{X}=[\begin{array}{cc}{\mathbf{A}}_{3\times 2}& {\mathbf{B}}_{3\times 2}\end{array}]$$
$$\mathbf{Y}=[\begin{array}{cc}\mathrm{a}& b\end{array}]$$

where the subscripts of \(\mathbf{A}\), \(\mathbf{B}\) denote their dimensions. \(a\) and \(b\) are scalars. Then \(\mathbf{X}\circ {\mathbf{Y}}^{T}\) is evaluated as

$$\mathbf{X}\circ {\mathbf{Y}}^{T}=\left[\begin{array}{cc}{\mathbf{A}}_{3\times 2}& {\mathbf{B}}_{3\times 2}\end{array}\right]\circ {\left[\begin{array}{cc}a& b\end{array}\right]}^{T}=a{\mathbf{A}}_{3\times 2}+b{\mathbf{B}}_{3\times 2}$$

It has the similar transpose property as matrix multiplication.

$${(\mathbf{X}\circ {\mathbf{Y}}^{T})}^{T}=\mathbf{Y}\circ {\mathbf{X}}^{T}$$

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Y., Ben-Tzvi, P. How a serpentine tail assists agile motions of kangaroo rats: a dynamics and control approach. Nonlinear Dyn 111, 14783–14803 (2023). https://doi.org/10.1007/s11071-023-08646-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-023-08646-w

Keywords

Navigation