Abstract The possibility of integrating bioinspired robots in groups of live social animals may constitute a valuable tool to study the basis of social behavior and uncover the fundamental determinants of animal functions and dysfunctions. In this study, we investigate the interactions between individual golden shiners (Notemigonus crysoleucas) and robotic fish swimming together in a water tunnel at constant flow velocity. The robotic fish is designed to mimic its live counterpart in the aspect ratio, body shape, dimension, and locomotory pattern. Fish positional preference with respect to the robot is experimentally analyzed as the robot's color pattern and tail-beat frequency are varied. Behavioral observations are corroborated by particle image velocimetry studies aimed at investigating the flow structure behind the robotic fish. Experimental results show that the time spent by golden shiners in the vicinity of the bioinspired robotic fish is the highest when the robot mimics their natural color pattern and beats its tail at the same frequency. In these conditions, fish tend to swim at the same depth of the robotic fish, where the wake from the robotic fish is stronger and hydrodynamic return is most likely to be effective.

Citation: 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. https://doi.org/10.1371/journal.pone.0077589 Editor: Eleni Vasilaki, University of Sheffield, United Kingdom Received: June 24, 2013; Accepted: September 10, 2013; Published: October 25, 2013 Copyright: © 2013 Polverino et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This research was supported by the National Science Foundation under Grant # CMMI-0745753. Additional support has been provided in part by the Honors Center of Italian Universities (H2CU) through a scholarship to G. Polverino and National Science Foundation under Grant # CMMI-0926791 and DGE-0741714. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

Introduction Thousands of fish species are known to aggregate at some stage of their life cycle in organized social groups commonly referred to as “shoals” [1]–[3]. Living in shoals allows fish to reduce the risk of predation [4]–[7] and the energetic costs of their motion [8]–[11]. The coordinated phenomenon of “schooling” is the macroscopic result of a complex transmission of signals within the shoal, in which fish tend to maintain uniform polarization and cohesion in nearly crystallized swimming formations [1], [12]. Such collective behavior is mediated by the integrated physiological system of muscles [13], organs, and senses that has evolved at the individual level as a valid alternative to living solitarily [1], [14], [15]. While it is generally accepted that several sensory cues are utilized by schooling fish to perceive their environment [16] and interact with their conspecifics [17], the quantification of the relative contribution of such cues is yet to be fully understood for several species [9], [15], [18]–[22]. In this context, the use of live stimuli in laboratory experiments only permits minimal flexibility for controlling and dissecting specific behavioral responses. Moreover, natural physiological fluctuations in such stimuli can introduce errors due to the inconsistency of the variables measured [23]. Robotics has been recently proposed as a viable means for enabling hypothesis-driven research in animal behavior, whereby robotic devices can be integrated into animal systems to serve as fully controllable and consistent experimental tools [24]–[26]. In this vein, robots with varying degree of biomimicry have been utilized to influence the behavior of several animal species across an ample set of experimental paradigms tailored to emphasize, and possibly dissect, select biological cues. Visual signaling from biologically-inspired robots has been used to investigate the behavior of birds [27]–[31], dogs [32], lizards [33], fish [22], [34]–[42], and rats [43]; salient chemical cues have been implemented on a miniature mobile robot to investigate social behavior of cockroaches [44]; audio feedback has been integrated in a model of a robotic squirrel to influence squirrels' behavior [45]; pulsing air currents created by robotic honeybees have been used to investigate honeybees' dance [46]; and hydrodynamic cues from a swimming robotic fish have been considered in [20] to modulate fish behavior in a water tunnel. While these efforts have demonstrated the feasibility of using robotics to influence animal behavior, dissecting and quantifying sensory cues in social animals are still untapped research questions. A particularly relevant area entails the analysis of the interplay between visual and flow cues in social freshwater fish. A variety of phenotypic characteristics observed in freshwater fish species are recognized as important factors in eliciting social interactions between conspecifics [18], [47]–[50]. Fish species used in laboratory studies, such as zebrafish, sticklebacks, and mosquitofish, respond to changes in stripe and color patterns of their conspecifics, and these features have been associated to their shoaling preferences, mating choices, and social ranks, respectively [18], [48], [49], [51]. The same features have been found to be determinants of attraction toward a robotic fish when its morphophysiological and locomotory features have been systematically varied in a series of preference tests [35]–[37]. Specifically, in this series of works it is demonstrated that the behavioral response of zebrafish individuals and small shoals varies as the aspect ratio, color pattern, and tail-beat frequency of a robotic fish is changed. Moreover, the attraction is maximized when the robotic fish most closely replicates its animal counterpart in its color, stripes, and aspect ratio. Fish swimming pattern is also a critical factor in shaping collective behavior [10], [52]–[55]. Laboratory experiments have demonstrated that fish can be repelled by chaotic and widely fluctuating flow conditions, while being attracted by vortical structures in predictable flows, from which they can harness energy [52], [56]. In [20], golden shiners swam in a water tunnel with a robotic fish whose tail-beat was systematically varied along with the flow speed. While findings in [20] have contributed to validating the hypothesis that the hydrodynamic return offered by a robotic fish is a determinant for robotic fish's attractiveness to live fish, the robot used therein was considerably larger than live fish. The unmatched size between live and robotic fish in [20] may act as a confound for elucidating the role of flow cues produced by fish locomotion on collective behavior. Indeed, fish social behavior is generally dependent on the size-class [57], [58]. Specifically, shoaling in golden shiners is found to be dependent on the size of the neighbors in [19], whereby individuals of the same size-class are preferred shoaling partners. Controlled animal replicas that incorporate several biologically relevant features from the target species, such as phenotypic cues and locomotion patterns [59], can yield further insight into the social behavior of fish. In this work, we employ two prototypes of robotic fish, whose engineering design was bioinspired to mimic the aspect ratio, body shape, size, and species-specific locomotion pattern observed in live golden shiner. The two prototypes differ in their color pattern that was varied to resemble either the typical pigmentation of their live counterpart or to offer an unnatural color phenotype. The objective of this study is to identify the determinants of attraction that regulate the collective behavior in social fish species when swimming together in a water tunnel. By using a reliable, consistent, and remotely controlled robotic platform, we test the hypothesis that, at a constant swimming velocity, a bioinspired robotic fish is able to elicit attraction in a live fish as a consequence of the visual and flow cues it offers. Specifically, the following predictions are expected to be met: i) fish attraction toward the robotic fish should vary as the visual cues offered by the robotic fish are varied, in agreement with similar observations for zebrafish in [35]–[37]; ii) fish attraction should vary as a function of the robotic fish tail-beat frequency, as suggested in [60] and observed in [20]; and iii) the highest attraction should be reached when both visual and flow cues from the live fish are simultaneously integrated in the robotic fish prototype.

Discussion Our results show that fish positional preference is affected by the color of the robotic fish, whereby a prototype with a bioinspired color pattern (Gray robot) is more attractive than a red replica (Red robot). This result is in line with experimental evidences on the role of visual cues in computer-animated images to elicit social responses in comparable fish species, such as sticklebacks [66], [67], mosquitofish [51], and zebrafish [47], [48], . Specifically, several phenotypic varieties of zebrafish, taxonomically listed in the Cyprinidae family together with golden shiner, are known to react differently to computer animations of their conspecifics depending on the similarities of their stripe pattern [47], [48] and color pigmentation [48]. Further studies have corroborated the evidence that zebrafish shoaling preference is affected by visual cues incorporated by both live [72] and robotic [35], [37], [73] stimuli. While the evolution of the stripe patterns is generally attributed to ecologic constraints and is associated with structurally complex habitats, the evolution of color patterns, not due camouflage or other ecologic constraints, is commonly related to fish mating choice [74]. Red phenotypic variants of golden shiners are not present in nature and other red-colored species do not co-inhabit water bodies where golden shiner is native [61]. Zebrafish ecology is, in this regard, similar to golden shiners, whereby red phenotypes do not exist and interaction with red-colored species is not documented [75]. Laboratory studies have demonstrated that shoaling preference in zebrafish is negatively affected by red pigmentations of animated images of their conspecifics [48], which are likely perceived as heterospecifics [48]. In line with [48], we observe that fish preference is significantly higher when the species-specific color pattern is experimentally integrated into the robotic prototype. The spatial preference of live fish in the test tank suggests that, beyond the visual cues offered by the robot, flow cues play an important role in shaping fish-robot interactions. The attraction induced by the robot tail-beat on fish is already known in the literature [20], [35]. Here, the robotic fish was designed to mimic the locomotion of golden shiners and match their morphology. The flow physics induced by the robotic fish tail-beat was measured with PIV and juxtaposed with the spatial preference of live fish to dissect the role of flow cues on the interaction. Despite the large amount of time spent by fish outside the focal region, we observe that the time spent by subjects in both the middle compartment (from the Side view) and behind the robot (from the Top view) were the highest when the Gray robot matched the tail-beat frequency of the live fish. Specifically, fish consistently preferred to follow the Gray robot rather than its red replica, spending a larger amount of time in the focal region behind the robotic fish (from the Top view) and in the middle of the water column (from the Side view). In other words, fish preferred to spend time following the Gray robot when its undulation matched their locomotion pattern at that flow speed. We hypothesize that such preference is due to the wake produced by the tail-beat of the robotic fish, which seeks to replicate the flow physics induced by the motion of a conspecific. The latter feature is addressed through the design of a miniature multi-link mechanism that allows for replicating the species-specific locomotory pattern of carangiform swimmers [64], wherein a large portion of the body undulates to propel the animal. Such interaction is likely to produce a hydrodynamic advantage for the live fish, which thus would follow the Gray robot to reduce its energy expenditure, in agreement with observations on other social carangiform swimmers [64]. The interpretation that fish preference for the robot is modulated by flow cues is supported by evidence in [20], where it is demonstrated that golden shiners tend to follow a larger robotic fish, whose morphology is not directly inspired by golden shiners, on the basis of its hydrodynamics. However, while hydrodynamic advantage is known to be a primary determinant of shoaling within conspecifics and heterospecifics [76], our results indicate that golden shiners respond differentially to the same flow cues induced by a morphophysiologically-inspired robotic fish as a function of its coloration. The study of robot-animal interaction is an interdisciplinary research field known as “ethorobotics” that is receiving increasing interest by both the engineering and biology communities. In this emerging context, robots can be designed to offer controlled stimuli in laboratory experiments toward dissecting salient behavioral responses. Robotic fish that incorporate biologically relevant attributes of live animals have been shown to influence fish behavior across a wide spectrum of sensory modalities [20], [22], . In this study, we have proposed an implementation of a robotic fish to investigate the interplay between visual and flow cues in the phenomenon of schooling in carangiform social fish.

Acknowledgments The authors would like to gratefully acknowledge Dr. A. L. Facci for the technical support on PIV measurements, Mr. M. Drago for the technical support on the design of the robotic fish prototype, Ms. L. Yang and Mr. K. Khan for their valuable help in performing the experiments, and Dr. S. Macri for the useful discussion and the assistance with the behavioral classification using the software Observer. The authors would also like to acknowledge the Wildlife Conservation Society's Department of Herpetology at the Bronx Zoo for providing the experimental animals.

Supporting Information Material S1. Supporting material on the visual aspect of the robotic fish, the measurement of golden shiners' tail-beat frequency, the motion tracking of the robotic fish, the particle image velocimetry analyses. https://doi.org/10.1371/journal.pone.0077589.s001 (DOCX)

Author Contributions Performed the experiments: GP PP. Analyzed the data: GP PP MP. Wrote the paper: GP PP MP. Developed the approach: GP MP.