Fighting fish love robots: mate discrimination in males of a highly territorial fish by using female-mimicking robotic cues

Romano, Donato; Benelli, Giovanni; Hwang, Jiang‐Shiou; Stefanini, Cesare

doi:10.1007/s10750-019-3899-6

Cited by 23 publications

(14 citation statements)

References 84 publications

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“…In the past, a variety of studies focused on living organisms interaction with robotic cues [31][32][33][34] and controlling the robot through BCI, but there have been few research on the control of teleoperation robot based on motor imagery EEG. Meanwhile, most of the previous research groups focus on the conventional two class or four class classification from EEG signals to get one or four control commands.…”

Section: Discussionmentioning

confidence: 99%

Motor Imagery Based Continuous Teleoperation Robot Control with Tactile Feedback

Bao-guo

et al. 2020

Electronics

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Brain computer interface (BCI) adopts human brain signals to control external devices directly without using normal neural pathway. Recent study has explored many applications, such as controlling a teleoperation robot by electroencephalography (EEG) signals. However, utilizing the motor imagery EEG-based BCI to perform teleoperation for reach and grasp task still has many difficulties, especially in continuous multidimensional control of robot and tactile feedback. In this research, a motor imagery EEG-based continuous teleoperation robot control system with tactile feedback was proposed. Firstly, mental imagination of different hand movements was translated into continuous command to control the remote robotic arm to reach the hover area of the target through a wireless local area network (LAN). Then, the robotic arm automatically completed the task of grasping the target. Meanwhile, the tactile information of remote robotic gripper was detected and converted to the feedback command. Finally, the vibrotactile stimulus was supplied to users to improve their telepresence. Experimental results demonstrate the feasibility of using the motor imagery EEG acquired by wireless portable equipment to realize the continuous teleoperation robot control system to finish the reach and grasp task. The average two-dimensional continuous control success rates for online Task 1 and Task 2 of the six subjects were 78.0% ± 6.1% and 66.2% ± 6.0%, respectively. Furthermore, compared with the traditional EEG triggered robot control using the predefined trajectory, the continuous fully two-dimensional control can not only improve the teleoperation robot system’s efficiency but also give the subject a more natural control which is critical to human–machine interaction (HMI). In addition, vibrotactile stimulus can improve the operator’s telepresence and task performance.

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Section: Discussionmentioning

confidence: 99%

Motor Imagery Based Continuous Teleoperation Robot Control with Tactile Feedback

Bao-guo

et al. 2020

Electronics

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“…The way of locomotion does not necessarily have to be identical to the locomotion of the organisms, as long as it does not disturb them in any way. Various approaches along these lines have been performed with fish robots, either with magnetic coupling or mounted on a rod ( Faria et al, 2010 ; Donati et al, 2016 ; Landgraf et al, 2016 ; Bonnet et al, 2017b ; Worm et al, 2017 ; Porfiri et al, 2019 ; Romano et al, 2019 ; Utter and Brown, 2020 ), with wheeled robots interacting with cockroach communities ( Halloy et al, 2007 ) or flocks of ducks ( Vaughan et al, 2000 ) and with a dancing robot with honeybee foragers ( Landgraf et al, 2010 ). In all these cases, the locomotion of the robot was achieved differently from the locomotion of the living animal counterparts, and the robots were of varying bio-mimetic perfection, some just emitting the key stimuli necessary for influencing the organisms ( Tinbergen, 1951 ).…”

Section: Towards a Proactive Contingency: Organismic Augmentationmentioning

confidence: 99%

Social Integrating Robots Suggest Mitigation Strategies for Ecosystem Decay

Schmickl

Szopek

Mondada

et al. 2021

Front. Bioeng. Biotechnol.

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We develop here a novel hypothesis that may generate a general research framework of how autonomous robots may act as a future contingency to counteract the ongoing ecological mass extinction process. We showcase several research projects that have undertaken first steps to generate the required prerequisites for such a technology-based conservation biology approach. Our main idea is to stabilise and support broken ecosystems by introducing artificial members, robots, that are able to blend into the ecosystem’s regulatory feedback loops and can modulate natural organisms’ local densities through participation in those feedback loops. These robots are able to inject information that can be gathered using technology and to help the system in processing available information with technology. In order to understand the key principles of how these robots are capable of modulating the behaviour of large populations of living organisms based on interacting with just a few individuals, we develop novel mathematical models that focus on important behavioural feedback loops. These loops produce relevant group-level effects, allowing for robotic modulation of collective decision making in social organisms. A general understanding of such systems through mathematical models is necessary for designing future organism-interacting robots in an informed and structured way, which maximises the desired output from a minimum of intervention. Such models also help to unveil the commonalities and specificities of the individual implementations and allow predicting the outcomes of microscopic behavioural mechanisms on the ultimate macroscopic-level effects. We found that very similar models of interaction can be successfully used in multiple very different organism groups and behaviour types (honeybee aggregation, fish shoaling, and plant growth). Here we also report experimental data from biohybrid systems of robots and living organisms. Our mathematical models serve as building blocks for a deep understanding of these biohybrid systems. Only if the effects of autonomous robots onto the environment can be sufficiently well predicted can such robotic systems leave the safe space of the lab and can be applied in the wild to be able to unfold their ecosystem-stabilising potential.

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“…The replica was fabricated using a 3D-printed mold (Ultimaker 2+, Ultimaker B.V., Geldermalsen, The Netherlands), where we poured a flexible silicone mixture (Smooth-On, Inc., Macungie, PA, USA), see Figure 2. The use of silicone instead of rigid material allows a more naturalistic bending of the replica's body during its motion through the experimental tank, which could increase its biomimicry and acceptance by the live zebrafish (Romano et al, 2017(Romano et al, , 2019a. The replica was then painted with silicone-based paint (Smooth-On, Inc., Macungie, PA,USA).…”

Section: Hardwarementioning

confidence: 99%

A Comparison of Individual Learning and Social Learning in Zebrafish Through an Ethorobotics Approach

et al. 2019

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Social learning is ubiquitous across the animal kingdom, where animals learn from group members about predators, foraging strategies, and so on. Despite its prevalence and adaptive benefits, our understanding of social learning is far from complete. Here, we study observational learning in zebrafish, a popular animal model in neuroscience. Toward fine control of experimental variables and high consistency across trials, we developed a novel robotics-based experimental test paradigm, in which a robotic replica demonstrated to live subjects the correct door to join a group of conspecifics. We performed two experimental conditions. In the individual training condition, subjects learned the correct door without the replica. In the social training condition, subjects observed the replica approaching both the incorrect door, to no effect, and the correct door, which would open after spending enough time close to it. During these observations, subjects could not actively follow the replica. Zebrafish increased their preference for the correct door over the course of 20 training sessions, but we failed to identify evidence of social learning, whereby we did not register significant differences in performance between the individual and social training conditions. These results suggest that zebrafish may not be able to learn a route by observation, although more research comparing robots to live demonstrators is needed to substantiate this claim.

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Fighting fish love robots: mate discrimination in males of a highly territorial fish by using female-mimicking robotic cues

Cited by 23 publications

References 84 publications

Motor Imagery Based Continuous Teleoperation Robot Control with Tactile Feedback

Motor Imagery Based Continuous Teleoperation Robot Control with Tactile Feedback

Social Integrating Robots Suggest Mitigation Strategies for Ecosystem Decay

A Comparison of Individual Learning and Social Learning in Zebrafish Through an Ethorobotics Approach

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