Animal-robot interactions

Our research develops and uses robotic devices that interact with animal groups to observe and modulate their behaviour, in order to better understand them, e.g. their collective decision making.

This work has goals in behavioural sciences, collective dynamics and systems modelling; and employs tools and techniques from mobile robotics, microengineering, machine learning, computer vision, and complex systems.

Honeybees and robots


photograph by ArtLifeLab Graz. Hardware by MOBOTS-EPFL

We are developing robotic devices that live inside beehives and continually interact with entire honeybee colonies. The robots modulate the internal hive environment with vibrations and heat; these are used to explore how behaviours can be steered at individual and colony levels (Ilgun et al, 2021). We have recently demonstrated the capacity of our robotic system to interact with an intact winter cluster, comprising thousands of animals (Barmak et al, 2023; see also our press release). This research is part of the FET-EU project HIVEOPOLIS, in which we also contribute to core systems (e.g., Komasilovs et al, 2024) and educational activities. Overall a main aim is to better understand how our long-term live-in robotics (Barmak et al, 2024) can support honeybees in an increasingly hostile environment for these crucial pollinators. 

Our previous work studied collective behaviours in honeybee-robot interactions in laboratory conditions (Schmickl et al 2021Halloy et al 2013Zahadat et al 2014), investigating how reactive thermal environments influence decision-making.

Fish and robots

Photographer: Catherine Leutenegger, EPFL

We are developing systems comprising of multiple mobile robots interacting with small groups of fish such as zebrafish (Danio rerio) and rummy-nose tetra (Hemigramus rhodostomus). The robotic agents (Bonnet et al 2017, Bonnet et al 2016, Papaspyros et al 2019, Papaspyros et al, 2023) were controlled via a closed-loop system using computer vision analysis (Bonnet et al 2017), and have been shown to be capable of integrating into groups of fish (Bonnet et al 2018) and modulating collective decisions (Bonnet et al 2018, Chemtob et al 2020). More generally, we work on modelling the dynamics of fish (Escodebo et al 2020), so to design robotic interactions with increased bio-acceptance (Papaspyros et al 2019). Most recently we have shown that  deep learning models of fish social interactions  are competitive with analytical approaches (Papaspyros et al, 2024) as well as being generalisable. 


Interspecies interactions mediated by bio-hybrid robots

Our research within the FET-EU project ASSISIbf included the
breakthrough of developing inter-species interactions between
honeybees and zebrafish, mediated via robots (Bonnet et al, 2019).

Our press release includes a further summary of this research:

Animals and robots – other research


  • The LEURRE project constructed the first robots that were shown to infiltrate an animal group – being accepted like conspecifics – and, through acting as “agent provocateur”, were able to modulate group decisions from within. (Halloy et al 2007). Here, our robots interacted with cockroaches.
  • We developed mobile robots that interacted with domestic chickens, (Gribovskiy et al 2018, 2008, 2012). This system made use of visual and auditory channels for both observation (animals ⇒ robots) and modulation (robots ⇒ animals). 
  • Across all animal-robot interaction studies, the robotic devices must be capable of transmitting cues or signals that are relevant to the animal, of sensing the animal’s response to the presented information, and finally of reacting to it. The design of such animal-interacting robots is highly non-trivial, depending on understanding the animals, modelling, robot design, and embodiment. We developed a general methodology to address these interconnected challenges (Mondada et al 2013).

Related publications


Biohybrid Superorganisms—On the Design of a Robotic System for Thermal Interactions With Honeybee Colonies

R. Barmak; D. N. Hofstadler; M. Stefanec; L. Piotet; R. Cherfan et al. 

IEEE Access. 2024. Vol. 12, p. 50849-50871. DOI : 10.1109/ACCESS.2024.3385658.

Architecture of a decentralised decision support system for futuristic beehives

V. Komasilovs; R. Mills; A. Kviesis; F. Mondada; A. Zacepins 

Biosystems Engineering. 2024. Vol. 240, p. 56-61. DOI : 10.1016/j.biosystemseng.2024.02.017.

Predicting the long-term collective behaviour of fish pairs with deep learning

V. Papaspyros; R. Escobedo; A. Alahi; G. Theraulaz; C. Sire et al. 

Journal of The Royal Society Interface. 2024. Vol. 21, num. 212. DOI : 10.1098/rsif.2023.0630.


Challenges and approaches in bridging the biomimicry gap in biohybrid systems of fish and robots

V. Papaspyros / F. Mondada (Dir.)  

Lausanne, EPFL, 2023. 

A biohybrid interaction framework for the integration of robots in animal societies

V. Papaspyros; D. Burnier; R. Cherfan; G. Theraulaz; C. Sire et al. 

IEEE Access. 2023-06-30.  p. 1-1. DOI : 10.1109/ACCESS.2023.3290960.

A robotic honeycomb for interaction with a honeybee colony

R. Barmak; M. Stefanec; D. N. Hofstadler; L. Piotet; S. Schönwetter-Fuchs-Schistek et al. 

Science Robotics. 2023-03-22. Vol. 8, num. 76. DOI : 10.1126/scirobotics.add7385.


A study model for reconstructing urban ecological niches

A. Ilgün; R. Mills; F. Mondada; T. Schmickl 

2022. Fifth International Conference on Structures and Architecture (ICSA2022), Aalborg, Denmark, July 6–8, 2022. p. 75-82.


Bio-Hybrid Systems for Ecosystem Level Effects

A. Ilgün; K. Angelov; M. Stefanec; S. Schönwetter-Fuchs; V. Stokanic et al. 

2021. The 2021 Conference on Artificial Life, July 19–23, 2021. DOI : 10.1162/isal_a_00396.

Social Integrating Robots Suggest Mitigation Strategies for Ecosystem Decay

T. Schmickl; M. Szopek; F. Mondada; R. Mills; M. Stefanec et al. 

Frontiers In Bioengineering And Biotechnology. 2021-05-24. Vol. 9, p. 612605. DOI : 10.3389/fbioe.2021.612605.


A data-driven method for reconstructing and modelling social interactions in moving animal groups

R. Escobedo; V. Lecheval; V. Papaspyros; F. Bonnet; F. Mondada et al. 

Philosophical Transactions of the Royal Society B: Biological Sciences. 2020-07-27. Vol. 375, num. 1807, p. 20190380. DOI : 10.1098/rstb.2019.0380.

Strategies to modulate zebrafish collective dynamics with a closed-loop biomimetic robotic system

Y. Chemtob; L. Cazenille; F. Bonnet; A. Gribovskiy; F. Mondada et al. 

Bioinspiration & Biomimetics. 2020-07-01. Vol. 15, num. 4, p. 046004. DOI : 10.1088/1748-3190/ab8706.


Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio

V. Papaspyros; F. Bonnet; B. E. Collignon; F. Mondada 

PLoS One. 2019-08-20. Vol. 14, num. 8, p. e0220559. DOI : 10.1371/journal.pone.0220559.

Shoaling with Fish: Using Miniature Robotic Agents to Close the Interaction Loop with Groups of Zebrafish Danio rerio

F. Bonnet; F. Mondada 

Springer, 2019.

Robots mediating interactions between animals for interspecies collective behaviors

F. Bonnet; R. Mills; M. Szopek; S. Schoenwetter-Fuchs; J. Halloy et al. 

Science Robotics. 2019-03-27. Vol. 4, num. 28, p. eaau7897. DOI : 10.1126/scirobotics.aau7897.


How to Blend a Robot Within a Group of Zebrafish: Achieving Social Acceptance Through Real-Time Calibration of a Multi-level Behavioural Model

L. Cazenille; Y. Chemtob; F. Bonnet; A. Gribovskiy; F. Mondada et al. 

2018-01-01. 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines (LM), Paris, FRANCE, Jul 17-20, 2018. p. 73-84. DOI : 10.1007/978-3-319-95972-6_9.

Follow the dummy: measuring the influence of a biomimetic robotic fish-lure on the collective decisions of a zebrafish shoal inside a circular corridor

F. Bonnet; J. Halloy; F. Mondada 

2018-04-26. Robosoft 2018: The first IEEE-RAS International Conference on Soft Robotics, Livorno, Italy, April 24-28, 2018. p. 504-509. DOI : 10.1109/ROBOSOFT.2018.8405376.

Designing a socially integrated mobile robot for ethological research

A. Gribovskiy; J. Halloy; J. Deneubourg; F. Mondada 

Robotics and Autonomous Systems. 2018-02-21. Vol. 103, p. 42-55. DOI : 10.1016/j.robot.2018.02.003.

Closed-loop interactions between a shoal of zebrafish and a group of robotic fish in a circular corridor

F. Bonnet; A. Gribovskiy; J. Halloy; F. Mondada 

Swarm Intelligence. 2018. Vol. 12, num. 3, p. 227-244. DOI : 10.1007/s11721-017-0153-6.

How mimetic should a robotic fish be to socially integrate into zebrafish groups ?

L. Cazenille; B. E. Collignon; Y. Chemtob; F. Bonnet; A. Gribovskiy et al. 

Bioinspiration & Biomimetics. 2018. Vol. 13, num. 2, p. 025001. DOI : 10.1088/1748-3190/aa8f6a.


Multi-robot control and tracking framework for bio-hybrid systems with closed-loop interaction

F. Bonnet; L. Cazenille; A. Gribovskiy; J. Halloy; F. Mondada 

2017. Robotics and Automation (ICRA), 2017 IEEE International Conference on, Singapore, Singapore, 29 May-3 June 2017. DOI : 10.1109/ICRA.2017.7989515.

Design of a modular robotic system that mimics small fish locomotion and body movements for ethological studies

F. Bonnet; L. Cazenille; A. Séguret; A. Gribovskiy; B. E. Collignon et al. 

International Journal of Advanced Robotic Systems. 2017. Vol. 14, num. 3, p. 1729881417706628. DOI : 10.1177/1729881417706628.

Shoaling with fish: using miniature robotic agents to close the interaction loop with groups of zebrafish Danio rerio

F. Bonnet / F. Mondada (Dir.)  

Lausanne, EPFL, 2017. 


Design Methods for Miniature Underwater Soft Robots

F. Bonnet; N. Crot; D. Burnier; F. Mondada 

2016. 6th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016), Singapore, June 26-29, 2016. p. 1365-1370. DOI : 10.1109/BIOROB.2016.7523823.


Infiltrating the Zebrafish Swarm: Design, Implementation and Experimental Tests of a Miniature Robotic Fish Lure for Fish-Robot Interaction Studies

F. Bonnet; Y. Kato; J. Halloy; F. Mondada 

2015. SWARM 2015: The First International Symposium on Swarm Behavior and Bio-Inspired Robotics, Kyoto, Japan, October 28-30, 2015. p. 239-246. DOI : 10.1007/s10015-016-0291-8.

Interacting with zebrafish using robotic agents

F. Bonnet; A. Séguet; L. Cazenille; M. Elias de Oliveira; B. Collignon et al. 

8th annual Swiss zebrafish meeting, Fribourg, Switzerland, April 10, 2015.


A Miniature Mobile Robot Developed to be Socially Integrated with Species of Small Fish

F. Bonnet; S. Binder; M. Elias de Oliveira; J. Halloy; F. Mondada 

2014. IEEE International Conference on Robotics and Biomimetics, Bali, Indonesia, December 5-10. p. 747-752. DOI : 10.1109/ROBIO.2014.7090421.

Social Adaptation of Robots for Modulating Self-Organization in Animal Societies

P. Zahadat; M. Bodi; Z. Salem; F. Bonnet; M. Elias de Oliveira et al. 

2014. 2nd FoCAS Workshop on Fundamentals of Collective Systems, London, UK, September 8th, 2014. p. 55-60. DOI : 10.1109/SASOW.2014.13.


ASSISI: Mixing Animals with Robots in a Hybrid Society

T. Schmickl; S. Bogdan; L. Correia; S. Kernbach; F. Mondada et al. 

2013. Living Machines, International Conference on Biomimetic and Biohybrid Systems, London, July 29 – August 2013, 2013. p. 441-443. DOI : 10.1007/978-3-642-39802-5_60.

Towards bio-hybrid systems made of social animals and robots

J. Halloy; F. Mondada; S. Kernbach; T. Schmickl 

2013. Living Machines, International Conference on Biomimetic and Biohybrid Systems, London, July 29 – August 2013, 2013. p. 384-386. DOI : 10.1007/978-3-642-39802-5_42.

A general methodology for the control of mixed natural-artificial societies

F. Mondada; A. Martinoli; N. Correll; A. Gribovskiy; J. I. Halloy et al. 

Handbook of Collective Robotics; Singapore: Pan Stanford Publishing, 2013. p. 547-586.


Building a safe robot for behavioral biology experiments

A. Gribovskiy; J. I. Halloy; J-L. Deneubourg; F. Mondada 

2012. IEEE International Conference on Robotics and Biomimetics (ROBIO 2012), Guangzhou, China, December 11-14, 2012. p. 582-587. DOI : 10.1109/ROBIO.2012.6491029.

Development of a mobile robot to study the collective behavior of zebrafish

F. Bonnet; P. Rétornaz; J. I. Halloy; A. Gribovskiy; F. Mondada 

2012. IEEE International Conference on Biomedical Robotics and Biomechatronics, Roma, Italy, June 24-28, 2012. DOI : 10.1109/BioRob.2012.6290826.


Animal-Robot Interaction for Ethological Studies

A. Gribovskiy / F. Mondada (Dir.)  

Lausanne, EPFL, 2011. 


The PoulBot: a mobile robot for ethological studies on domestic chickens

A. Gribovskiy; J. I. Halloy; J-L. Deneubourg; F. Mondada 

Symposium on AI-Inspired Biology (AIIB).

Towards Mixed Societies of Chickens and Robots

A. Gribovskiy; J. I. Halloy; J-L. Deneubourg; H. Bleuler; F. Mondada 

2010. The IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010), Taipei, Taiwan, October 18-22, 2010. p. 4722-4728. DOI : 10.1109/IROS.2010.5649542.


Real-Time Audio-Visual Calls Detection System for a Chicken Robot

A. Gribovskiy; F. Mondada 

2009. 14th International Conference on Advanced Robotics (ICAR 2009), Munich, Germany, July 22-26, 2009. p. 1-6.

Design of Collision Avoidance System for a Chicken Robot Based on Fuzzy Relation Equations

A. Gribovskiy; F. Mondada 

2009. 2009 IEEE International Conference on Fuzzy Systems, Jeju, Korea, August 20-24, 2009. p. 1851-1856. DOI : 10.1109/FUZZY.2009.5277298.


Audio-visual detection of multiple chirping robots

A. Gribovskiy; F. Mondada 

2008. Intelligent Autonomous Systems 10, Baden Baden, Germany, July 23-26, 2008. p. 324-331. DOI : 10.3233/978-1-58603-887-8-324.


Social Integration of Robots into Groups of Cockroaches to Control Self-Organized Choices

J. Halloy; G. Sempo; G. Caprari; C. Rivault; M. Asadpour et al. 

Science. 2007. Vol. 318, num. 5853, p. 1155-1158. DOI : 10.1126/science.1144259.