A Biomimetic Neuronal Network-Based Controller for Guided Helicopter Flight

1. Ayers, J., Rulkov, N., Knudsen, D., Kim, Y.-B., Volkovskii, A., Selverston, A.: Controlling Underwater Robots with Electronic Nervous Systems. Appied Bionics and Biomimetics 7, 57–67 (2010)

   Article  Google Scholar 

2. Ayers, J., Blustein, D., Westphal, A.: A Conserved Biomimetic Control Architecture for Walking, Swimming and Flying Robots. In: Prescott, T.J., Lepora, N.F., Mura, A., Verschure, P.F.M.J. (eds.) Living Machines 2012. LNCS, vol. 7375, pp. 1–12. Springer, Heidelberg (2012)

   Chapter  Google Scholar 

3. Ayers, J., Witting, J.: Biomimetic Approaches to the Control of Underwater Walking Machines. Phil. Trans. R. Soc. Lond. A 365, 273–295 (2007)

   Article  Google Scholar 

4. Baader, A., Schfer, M.: The perception of the visual flow field by flying locusts: A behavioural and neuronal analysis. J. Exp. Biol. 165, 137–160 (1992)

   Google Scholar 

5. Blustein, D., Rosenthal, N., Ayers, J.: Designing and implementing nervous system simulations on LEGO robots. J of Visualized Experiments (in press, 2013)

   Google Scholar 

6. Blustein, D., Westphal, A., Ayers, J.: Optical flow mediates biomimetic odometry on an autonomous helicopter (in preparation, 2013)

   Google Scholar 

7. Boles, L.C., Lohmann, K.J.: True navigation and magnetic maps in spiny lobsters. Nature 421(6918), 60–63 (2003)

   Article  Google Scholar 

8. Chahl, J., Rosser, K., Mizutani, A.: Bioinspired optical sensors for unmanned aerial systems. In: Proceedings of SPIE: Bioinspiration, Biomimetics, and Bioreplication, vol. 7975, pp. 0301–0311 (2011)

   Google Scholar 

9. Conroy, J., Gremillion, G., Ranganathan, B., Humbert, J.S.: Implementation of wide-field integration of optic flow for autonomous quadrotor navigation. Auton. Robot. 27(3), 189–198 (2009)

   Article  Google Scholar 

10. Dantu, K., Kate, B., Waterman, J., Bailis, P., Welsh, M.: Programming micro-aerial vehicle swarms with karma. In: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems. ACM (2011)

    Google Scholar 

11. Dickinson, M.H., Tu, M.S.: The function of dipteran flight muscle. Comparative Biochemistry and Physiology Part A: Physiology 116(3), 223–238 (1997)

    Article  Google Scholar 

12. Duhamel, P.-E.J., Perez-Arancibia, N.O., Barrows, G.L., Wood, R.J.: Biologically Inspired Optical-Flow Sensing for Altitude Control of Flapping-Wing Microrobots. IEEE/ASME Trans Mechatron 18(2), 556–568 (2013)

    Article  Google Scholar 

13. Dyer, F.C.: The biology of the dance language. Annual Review of Entomology 47(1), 917–949 (2002)

    Article  MathSciNet  Google Scholar 

14. Dyer, F.C., Dickinson, J.A.: Sun-compass learning in insects: Representation in a simple mind. Current Directions in Psychological Science 5(3), 67–72 (1996)

    Article  Google Scholar 

15. Finio, B.M., Wood, R.J.: Open-loop roll, pitch and yaw torques for a robotic bee. In: IEEE/RSJ International Conf. on Intelligent Robots and Systems, IROS (2012)

    Google Scholar 

16. Fraser, P.J.: Statocysts in Crabs: Short-Term Control of Locomotion and Long-Term Monitoring of Hydrostatic Pressure. Biol. Bull. 200(2), 155–159 (2001)

    Article  Google Scholar 

17. Ibbotson, M.: Wide-field motion-sensitive neurons tuned to horizontal movement in the honeybee, Apis mellifera. J. Comp. Physiol. A: Neuroethology, Sensory, Neural, and Behavioral Physiology 168(1), 91–102 (1991)

    Article  Google Scholar 

18. Joesch, M., Weber, F., Eichner, H., Borst, A.: Functional Specialization of Parallel Motion Detection Circuits in the Fly. J.Neuroscience 33(3), 902–905 (2013)

    Article  Google Scholar 

19. Kate, B., Waterman, J., Dantu, K., Welsh, M.: Simbeeotic: A simulator and testbed for micro-aerial vehicle swarm experiments. In: Proceedings of the 11th International Conference on Information Processing in Sensor Networks. ACM (2012)

    Google Scholar 

20. Kennedy, D., Davis, W.J.: Organization of Invertebrate Motor Systems. Handbook of Physiology. The organization of invertebrate motor systems. In: Geiger, S.R., Kandel, E.R., Brookhart, J.M., Mountcastle, V.B. (eds.) Handbook of Physiology, sec. I, vol. I, part 2., pp. 1023–1087. Amer. Physiol. Soc, Bethesda (1977)

    Google Scholar 

21. Kiehn, O.: Development and functional organization of spinal locomotor circuits. Current Opinion in Neurobiology 21(1), 100–109 (2011)

    Article  Google Scholar 

22. Lobo, J., Ferreira, J.F., Dias, J.: Bioinspired visuo-vestibular artificial perception system for independent motion segmentation. In: Second International Cognitive Vision Workshop, ECCV 9th European Conference on Computer Vision, Graz, Austria (2006)

    Google Scholar 

23. Lu, J., Yang, J., Kim, Y.B., Ayers, J.: Low Power, High PVT Variation Tolerant Central Pattern Generator Design for a Bio-hybrid Micro Robot. In: IEEE International Midwest Symposium on Circuits and Systems, vol. 55, pp. 782–785 (2012)

    Google Scholar 

24. Ma, K.Y., Chirarattananon, P., Fuller, S.B., Wood, R.J.: Controlled Flight of a Biologically Inspired. Insect-Scale Robot. Science 340(6132), 603–607 (2013)

    Google Scholar 

25. Paulk, A., Millard, S.S., van Swinderen, B.: Vision in Drosophila: Seeing the World Through a Model’s Eyes. Annual Review of Entomology 58, 313–332 (2013)

    Article  Google Scholar 

26. Pearson, K.G.: Common principles of motor control in vertebrates and invertebrates. Annu.Rev.Neurosci. 16, 265–297 (1993)

    Article  Google Scholar 

27. Peirce, J.: PsychoPy - Psychophysics software in Python. J. Neurosci. Methods 162, 8–13 (2007)

    Article  Google Scholar 

28. Prescott, T.J., Lepora, N.F., Mura, A., Verschure, P.F.M.J. (eds.): Living Machines 2012. LNCS, vol. 7375. Springer, Heidelberg (2012)

    Google Scholar 

29. Rabinovich, M.I., Selverston, A., Abarbanel, H.D.I.: Dynamical principles in neuroscience. Reviews of Modern Physics 78(4), 1213–1265 (2006)

    Article  Google Scholar 

30. Rulkov, N.F.: Modeling of spiking-bursting neural behavior using two-dimensional map. Phys.Rev. E 65, 041922 (2002)

    Article  MathSciNet  Google Scholar 

31. Rutkowski, A.J., Miller, M.M., Quinn, R.D., Willis, M.A.: Egomotion estimation with optic flow and air velocity sensors. Biol. Cybern. 104(6), 351–367 (2011)

    Article  MathSciNet  MATH  Google Scholar 

32. Sarpeshkar, R.: Analog versus digital: extrapolating from electronics to neurobiology. Neural Computation 10(7), 1601–1638 (1998)

    Article  Google Scholar 

33. Srinivasan, M.V.: Honey bees as a model for vision, perception, and cognition. Annual Review of Entomology 55, 267–284 (2010)

    Article  Google Scholar 

34. Srinivasan, M.V.: Honeybees as a model for the study of visually guided flight, navigation, and biologically inspired robotics. Physiol Reviews 91(2), 413–460 (2011)

    Article  Google Scholar 

35. Srinivasan, M.V.: Visual control of navigation in insects and its relevance for robotics. Current Opinion in Neurobiology 21(4), 535–543 (2011)

    Article  Google Scholar 

36. Srinivasan, M., Zhang, S., Lehrer, M., Collett, T.: Honeybee navigation en route to the goal: visual flight control and odometry. J. Exp. Biol. 199, 237–244 (1996)

    Google Scholar 

37. Stein, P.S.G., Grillner, S., Selverston, A.I., Stuart, D.: Neurons, Networks and Motor Behavior. MIT Press, Cambridge (1997)

    Google Scholar 

38. Teoh, Z.E., Fuller, S.B., Chirarattananon, P.: A hovering flapping-wing microrobot with altitude control and passive upright stability. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3209–3216 (2012)

    Google Scholar 

39. Webb, B.: Can robots make good models of biological behaviour? Behav. Brain Sci. 24(6), 1033–1050 (2001)

    Google Scholar 

40. Webb, B.: Robots in invertebrate neuroscience. Nature 417(6886), 359–363 (2002)

    Article  Google Scholar 

41. Webb, B., Reeve, R.: Reafferent or redundant: integration of phonotaxis and optomotor behavior in crickets and robots. Adaptive Behavior 11(3), 137–158 (2003)

    Article  Google Scholar 

42. Westphal, A., Ayers, J.: A neuronal compass for autonomous biomimetic robots (in preparation, 2013)

    Google Scholar 

43. Westphal, A., Rulkov, N., Ayers, J., Brady, D., Hunt, M.: Controlling a lamprey-based robot with an electronic nervous system. Smart Struct. Sys. 8(1), 37–54 (2011)

    Google Scholar 

44. Wiersma, C.A., Yamaguchi, T.: Integration of visual stimuli by the crayfish central nervous system. J. Exp. Biol. 47(3), 409–431 (1967)

    Google Scholar 

45. Wood, R.J., Avadhanula, S., Steltz, E., Seeman, M., Entwistle, J., Bachrach, A., Barrows, G., Sanders, S.: An autonomous palm-sized gliding micro air vehicle. IEEE Robotics and Automation Magazine 14(2), 82–91 (2007)

    Article  Google Scholar 

46. Yorozu, S., Wong, A., Fischer, B., Dankert, H., Kernan, M., Kamikouchi, A., Ito, K., Anderson, D.: Distinct sensory representations of wind and near-field sound in the Drosophila brain. Nature 458, 201–205 (2009)

    Article  Google Scholar 

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