Abstract
In this chapter, we focus on the use of robotic fish in animal behavior studies. Specifically, we describe the design and control of a low-cost robot along with accompanying enabling technologies for use in animal experiments. The robotic fish appearance and movement are inspired by the zebrafish animal model. The robot is capable of autonomous underwater operation. Two behavioral studies demonstrate the use of the robotic fish to test hypotheses on zebrafish social behavior. In the first study exploring zebrafish preference in a binary choice test, we find that the robot is able to elicit attraction in both individuals and small shoals when the other alternative is an empty compartment. At the same time, between conspecifics and the robot, zebrafish prefer the former, highlighting design choices that need further improvement. The second study describes the interaction between the robot and shoals of zebrafish in a free-swimming environment. The robot swims autonomously along predefined circular trajectories at three different speeds, corresponding to increasing tail-beat frequency. The robot is found to modulate zebrafish shoal cohesion, confirming expectations from the preference study result. In summary, the robotic fish platform described in this chapter provides a viable and fully controllable three-dimensional interactive tool for animal behavior experiments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The experimental procedure was approved by Polytechnic Institute of New York University (now New York University Polytechnic School of Engineering) Animal Welfare Oversight Committee AWOC-2011-101.
- 2.
Experiments followed protocol numbers AWOC-2012-101 and AWOC-2013-103 that were approved by the Animal Welfare Oversight Committee of the Polytechnic Institute of New York University (now New York University Polytechnic School of Engineering).
References
Boissy A (1995) Fear and fearfulness in animals. Q Rev Biol 70(2):165–191
Krause J, Winfield AFT, Deneubourg J (2011) Interactive robots in experimental biology. Trends Ecol Evol 26(7):369–375
Rossi C, Coral W, Barrientos A (2012) Robotic fish to lead the school. In: Palstra AP, Planas JV (eds) Swimming physiology of fish. Springer, New York, pp 407–421
Ward AJW, Sumpter DJT, Couzin ID, Hart PJB, Krause J (2008) Quorum decision-making facilitates information transfer in fish shoals. Proc Natl Acad Sci USA 105(19):6948–6953
Partan SR, Larco CP, Owens MJ (2009) Wild tree squirrels respond with multisensory enhancement to conspecific robot alarm behaviour. Anim Behav 77(5):1127–1135
Halloy J, Sempo G, Caprari G, Rivault C, Asadpour M, Tâche F, Saïd I, Durier V, Canonge S, Amé JM, Detrain C, Correll N, Martinoli A, Mondada F, Siegwart R, Deneubourg JL (2007) Social integration of robots into groups of cockroaches to control self-organized choices. Science 318(5853):1155–1158
Spinello C, Macrì S, Porfiri M (2013) Acute ethanol administration affects zebrafish preference for a biologically-inspired robot. Alcohol 47(5):391–398
Todd DJ (1993) Mobile robots-the lessons from nature. Robot Biol Syst Towards New Bionics 102(1):193–206
Webb B (2002) Can robots make good models of biological behaviour? Behav Brain Sci 24(06):1033–1050
Tokekar P, Branson E, Vander Hook J, Isler V (2013) Tracking aquatic invaders: autonomous robots for monitoring invasive fish. Robot Autom Mag 20(3):33–41
Faria JJ, Dyer JRG, Clément RO, Couzin ID, Holt N, Ward AJW, Waters D, Krause J (2010) A novel method for investigating the collective behaviour of fish: introducing ‘Robofish’. Behav Ecol Sociobiol 64(8):1–8
Marras S, Porfiri M (2012) Fish and robots swimming together: attraction towards the robot demands biomimetic locomotion. J R Soc Interface 9(73):1856–1868
Cianca V, Bartolini T, Porfiri M, Macrì S (2013) A robotics-based behavioral paradigm to measure anxiety-related responses in zebrafish. PLoS ONE 8(7):e69661
Kopman V, Laut J, Polverino G, Porfiri M (2013) Closed-loop control of zebrafish response using a bioinspired robotic-fish in a preference test. J R Soc Interface 10(78):20120540
Butail S, Bartolini T, Porfiri M (2013) Collective response of zebrafish shoals to a free-swimming robotic fish. PLoS ONE 8(10):e76123
Miklósi A, Andrew RJ (2006) The zebrafish as a model for behavioral studies. Zebrafish 3(2):227–234
Gerlai R (2010) Zebrafish antipredatory responses: a future for translational research? Behav Brain Res 207(2):223–231
Kalueff AV, Stewart AM (eds) (2012) Zebrafish protocols for neurobehavioral research. Humana Press, New York
Ladu F, Bartolini T, Panitz S, Chiarotti F, Butail S, Macrì S & Porfiri M (2015) Live predators, robots, and computer-animated images elicit differential avoidance responses in zebrafish, Zebrafish. doi: 10.1089/zeb.2014.1041
Polverino G, Abaid N, Kopman V, Macrì S, Porfiri M (2012) Zebrafish response to robotic fish: preference experiments on isolated individuals and small shoals. Bioinspir Biomim 7(3):036019
Abaid N, Bartolini T, Macrì S, Porfiri M (2012) Zebrafish responds differentially to a robotic fish of varying aspect ratio, tail beat frequency, noise, and color. Behav Brain Res 233(2):545–553
Polverino G, Porfiri M (2013) Mosquitofish (Gambusia affinis) responds differentially to a robotic fish of varying swimming depth and aspect ratio. Behav Brain Res 250(1):133–138
Polverino G, Porfiri M (2013) Zebrafish (Danio rerio) behavioural response to bioinspired robotic fish and mosquitofish (Gambusia affinis). Bioinspir Biomim 8(4):044001
Polverino G, Phamduy P, Porfiri M (2013) Fish and robots swimming together in a water tunnel: robot color and tail-beat frequency influence fish behavior. PLoS ONE 8(10):e77589
Abaid N, Marras S, Fitzgibbons C, Porfiri M (2013) Modulation of risk-taking behaviour in golden shiners (Notemigonus crysoleucas) using robotic fish. Behav Process 100:9–12
Butail S, Ladu F, Spinello D, Porfiri M (2014) Information flow in animal-robot interactions. Entropy (Spec Iss Inf Dyn Syst Complex Syst) 16(3):1315–1330
Butail S, Polverino G, Phamduy P, Del Sette F, Porfiri M (2014) Influence of robotic shoal size, configuration, and activity on zebrafish behavior in a free-swimming environment. Behav Brain Res 275:269–280
Phamduy P, Polverino G, Fuller RC, Porfiri M (2014) Fish and robot dancing together: bluefin killifish females respond differently to the courtship of a robot with varying color morphs. Bioinspir Biomim 9(3):036021
Aureli M, Porfiri M (2010) Coordination of self-propelled particles through external leadership. Europhys Lett 92(4):40004
Aureli M, Fiorilli F, Porfiri M (2012) Portraits of self-organization in fish schools interacting with robots. Phys D Nonlinear Phenom 241(9):908–920
Kopman V, Laut J, Acquaviva F, Rizzo A, Porfiri M (2014) Dynamic modeling of a robotic fish propelled by a compliant tail. IEEE J Ocean Eng PP(99):1–13
Strefling PC, Helium AM, Mukherjee R (2012) Modeling, simulation, and performance of a synergistically propelled ichthyoid. IEEE/ASME Trans Mechatron 17(1):36–45
Low KH, Chong CW (2010) Parametric study of the swimming performance of a fish robot propelled by a flexible caudal fin. Bioinspir Biomim 5(4):046002
Barrett DS, Triantafyllou MS, Yue DKP, Grosenbaugh MA, Wolfgang MJ (1999) Drag reduction in fish-like locomotion. J Fluid Mech 392:183–212
Shao J, Wang L, Yu J (2008) Development of an artificial fish-like robot and its application in cooperative transportation. Control Eng Pract 16(5):569–584
Malec M, Morawski M, Zajac J (2010) Fish-like swimming prototype of mobile underwater robot. J Autom Mobile Robot Intell Syst 4:25–30
Liu J, Hu H (2010) Biological inspiration: from carangiform fish to multi-joint robotic fish. J Bionic Eng 7(1):35–48
Morgansen KA, Triplett BI, Klein DJ (2007) Geometric methods for modeling and control of free-swimming fin-actuated underwater vehicles. IEEE Trans Robot 23(6):1184–1199
Guo J (2006) A waypoint-tracking controller for a biomimetic autonomous underwater vehicle. Ocean Eng 33(17):2369–2380
Alvarado PV y, Youcef-Toumi K (2006) Design of machines with compliant bodies for biomimetic locomotion in liquid environments. J Dyn Syst Meas Control 128(1):3–13
Kopman V, Porfiri M (2012) Design, modeling, and characterization of a miniature robotic-fish for research and education in biomimetics and bioinspiration. IEEE/ASME Trans Mechatron 18(2):471–483
Abaid N, Kopman V, Porfiri M (2013) An attraction toward engineering careers: the story of a Brooklyn outreach program on biomimetics, underwater robotics, and marine science for K-12 students. IEEE Robot Autom Mag 20(2):31–39
Laut J, Bartolini T, Porfiri M (2014) Bioinspiring an interest in STEM. IEEE Trans Educ 58(1):48–55
Abaid N, Bernhardt J, Frank JA, Kapila V, Kimani D, Porfiri M (2013) Controlling a robotic fish with a smart phone. Mechatronics 23(5):491–496
Abaid N, Yuvienco C, Kapil V, Iskander M (2011) Mechatronics mania at the inaugural USA science and engineering festival. IEEE Control Syst Mag 31(5):105–124
Blaser R, Gerlai R (2006) Behavioral phenotyping in zebrafish: comparison of three behavioral quantification methods. Behav Res Methods 38(3):456–469
Pérez-Escudero A, Vicente-Page J, Hinz RC, Arganda S, de Polavieja GG (2014) idTracker: tracking individuals in a group by automatic identification of unmarked animals. Nat Methods 11:743–748
Delcourt J, Denoël M, Ylieff M, Poncin P (2013) Video multitracking of fish behaviour: a synthesis and future perspectives. Fish Fish 14:186–204
Dell AI, Bender JA, Branson K, Couzin ID, de Polavieja GG, Noldus LP, et al. (2014) Automated image-based tracking and its application in ecology. Trends Ecol Evol 29:417–428
Kuhn HW (1955) The Hungarian method for the assignment problem. Nav Res Logist Q 2:83–97
Ladu F, Butail S, Macrì S, Porfiri M (2014) Sociality modulates the effects of ethanol in zebrafish. Alcohol Clin Exp Res 38(7):2096–2104
Carson C, Belongie S (2002) Blobworld: image segmentation using expectation-maximization and its application to image querying. IEEE Trans Pattern Anal Mach Intell 24(8):1026–1038
Lieschke GJ, Currie PD (2007) Animal models of human disease: zebrafish swim into view. Nat Rev Genet 8(5):353–367
Grunwald DJ, Eisen JS (2002) Headwaters of the zebrafish—emergence of a new model vertebrate. Nat Rev Genet 3(9):717–724
Mathur P, Guo S (2010) Use of zebrafish as a model to understand mechanisms of addiction and complex neurobehavioral phenotypes. Neurobiol Dis 40(1):66–72
Gerlai R (2012) Using zebrafish to unravel the genetics of complex brain disorders. In: Current topics in behavioral neurosciences, behavioral neurogenetic, vol 12. Springer, Berlin, pp 3–24
Goldsmith JR, Jobin C (2012) Think small: zebrafish as a model system of human pathology. J Biomed Biotechnol 2012:817341
Kalueff AV, Steward AM, Gerlai R (2014) Zebrafish as an emerging model for studying complex brain disorders. Trends Pharmacol Sci 35(2):63–75
Stewart AM, Nguyen M, Wong K, Poudel MK, Kalueff AV (2014) Developing zebrafish models of autism spectrum disorder (ASD). Prog Neuro-Psychopharmacol Biol Psychiatry 50:27–36
Laale HW (1977) The biology and use of zebrafish, Brachydanio rerio in fisheries research. A literature review. J Fish Biol 10(2):121–173
Buske C, Gerlai R (2011) Shoaling develops with age in Zebrafish (Danio rerio). Prog. Neuro-Psychopharmacol Biol Psychiatry 35(6):1409–1415
Saverino C, Gerlai R (2008) The social zebrafish: behavioral responses to conspecific, heterospecific, and computer animated fish. Behav Brain Res 191(1):77–87
Pritchard VL, Lawrence J, Butlin RK, Krause J (2001) Shoal choice in zebrafish, Danio rerio: the influence of shoal size and activity. Anim Behav 62(6):1085–1088
Bass SLS, Gerlai R (2008) Zebrafish (Danio rerio) responds differentially to stimulus fish: the effects of sympatric and allopatric predators and harmless fish. Behav Brain Res 186(1):107–117
Snekser JL, Ruhl N (2010) The influence of sex and phenotype on shoaling decisions in zebrafish. Int J Comp Psychol 23(1):70–81
Cahill G (2002) Clock mechanisms in zebrafish. Cell Tissue Res 309(1):27–34
McDonald JH (2009) Handbook of biological statistics. Sparky House Publishing, Baltimore
Wong K, Elegante M, Bartels B, Elkhayat S, Tien D, Roy S, Goodspeed J, Suciu C, Tan J, Grimes C, Chung A, Rosenberg M, Gaikwad S, Denmark A, Jackson A, Kadri F, Chung KM, Stewart A, Gilder T, Beeson E, Zapolsky I, Wu N, Cachat J, Kalueff AV (2010) Analyzing habituation responses to novelty in zebrafish (Danio rerio). Behav Brain Res 208(2):450–457
Guo S, Fukuda T, Asaka K (2003) A new type of fish-like underwater microrobot. IEEE/ASME Trans Mechatron 8(1):136–141
Aureli M, Kopman V, Porfiri M (2010) Free-locomotion of underwater vehicles actuated by ionic polymer metal composites. IEEE/ASME Trans Mechatron 15(4):603–614
Chen Z, Shatara S, Tan X (2010) Modeling of biomimetic robotic fish propelled by an ionic polymer–metal composite caudal fin. IEEE/ASME Trans Mechatron 15(3):448–459
Chen Z, Um TI, Bart-Smith H (2011) A novel fabrication of ionic polymer–metal composite membrane actuator capable of 3-dimensional kinematic motions. Sens Actuators A Phys 168(1):131–139
Cen L, Erturk A (2013) Bio-inspired aquatic robotics by untethered piezohydroelastic actuation. Bioinspir Biomim 8(1):016006
Acknowledgments
This research was supported by National Science Foundation under grants CMMI- 0745753, DGE-0741714, CMMI-1129820, and CMMI-1433670. The authors would also like to thank Giovanni Polverino, Vladislav Kopman, and Tiziana Bartolini who have contributed to the research efforts summarized in this chapter.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Butail, S., Abaid, N., Macrì, S., Porfiri, M. (2015). Fish–Robot Interactions: Robot Fish in Animal Behavioral Studies. In: Du, R., Li, Z., Youcef-Toumi, K., Valdivia y Alvarado, P. (eds) Robot Fish. Springer Tracts in Mechanical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46870-8_12
Download citation
DOI: https://doi.org/10.1007/978-3-662-46870-8_12
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46869-2
Online ISBN: 978-3-662-46870-8
eBook Packages: EngineeringEngineering (R0)