Vaios Papaspyros

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

Daniel Burnier, Francesco Mondada, Vaios Papaspyros

The collective behavior of animals has been traditionally studied through observation, quantitative models of behavior, and devices of low intelligence. Nowadays, the advancements in the field of robotics allow for closed-loop experiments that occur in real-time, and for artificial agents that intelligently and autonomously blend into hybrid groups of animals and robots (i.e., biohybrid groups). Such systems provide scientists with the opportunity to study the social interactions that govern collective behavior from within the group of animals, either by mimicking them or by introducing precise stimuli to elicit and study their response. In this work, we introduce an open source Biohybrid Observation and Interaction (BOBI) platform for small animals, which consists of 3 main components: 1) an experimental setup; 2) a wheeled mobile robot called LureBot; 3) their software. We demonstrate the software and hardware design aspects that make BOBI stand out compared to our previous system and similarly purposed systems. Finally, we demonstrate our methodologies and the new robot’s agility, by conducting a set of preliminary experiments with rummy-nose tetra (Hemigrammus rhodostomus) fish, where we study: 1) the response of one fish swimming with a biomimetic and a non-biomimetic lure; 2) the robot behavior when the robot interacts biomimetically and in closed loop with the wall alone, with 1 fish, and with 4 fish. The experiments show that fish strongly prefer biomimetic lures, and that the robot is consistently successful in engaging in social interactions with the fish.

2023

The role of feedback and guidance as intervention methods to foster computational thinking in educational robotics learning activities for primary school

Bernard Baumberger, Evgeniia Bonnet, Christian Giang, Francesco Mondada, Vaios Papaspyros, Jean-Philippe Pellet

Computational thinking (CT) is considered an emerging competence domain linked to 21st-century competences, and educational robotics (ER) is increasingly recognised as a tool to develop CT competences. This is why researchers recommend developing intervention methods adapted to classroom practice and providing explicit guidelines to teachers on integrating ER activities. The present study thus addresses this challenge. Guidance and feedback were considered as critical intervention methods to foster CT competences in ER settings. A between-subjects experiment was conducted with 66 students aged 8 to 9 in the context of a remote collaborative robot programming mission, with four experimental conditions. A two-step strategy was employed to report students' CT competence (their performance and learning process). Firstly, the students' CT learning gains were measured through a pre-post-test design. Secondly, video analysis was used to identify the creative computational problem-solving patterns involved in the experimental condition that had the most favourable impact on the students’ CT scores. Results show that delayed feedback is an effective intervention method for CT development in ER activities. Subject to delayed feedback, students are better at formulating the robot behaviour to be programmed, and, thus, such a strategy reinforces the anticipation process underlying the CT.

2022

Exploring a Handwriting Programming Language for Educational Robots

Barbara Bruno, Christian Giang, Taavet Kangur, Laura Mathex, Francesco Mondada, Vaios Papaspyros

Recently, introducing computer science and educational robots in compulsory education has received increasing attention. However, the use of screens in classrooms is often met with resistance, especially in primary school. To address this issue, this study presents the development of a handwriting-based programming language for educational robots. Aiming to align better with existing classroom practices, it allows students to program a robot by drawing symbols with ordinary pens and paper. Regular smartphones are leveraged to process the hand-drawn instructions using computer vision and machine learning algorithms, and send the commands to the robot for execution. To align with the local computer science curriculum, an appropriate playground and scaffolded learning tasks were designed. The system was evaluated in a preliminary test with eight teachers, developers and educational researchers. While the participants pointed out that some technical aspects could be improved, they also acknowledged the potential of the approach to make computer science education in primary school more accessible.

Springer, Cham2021

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

Frank Bonnet, Francesco Mondada, Vaios Papaspyros

Group-living organisms that collectively migrate range from cells and bacteria to human crowds, and include swarms of insects, schools of fish, and flocks of birds or ungulates. Unveiling the behavioural and cognitive mechanisms by which these groups coordinate their movements is a challenging task. These mechanisms take place at the individual scale and can be described as a combination of interactions between individuals and interactions between these individuals and the physical obstacles in the environment. Thanks to the development of novel tracking techniques that provide large and accurate datasets, the main characteristics of individual and collective behavioural patterns can be quantified with an unprecedented level of precision. However, in a large number of studies, social interactions are usually described by force map methods that only have a limited capacity of explanation and prediction, being rarely suitable for a direct implementation in a concise and explicit mathematical model. Here, we present a general method to extract the interactions between individuals that are involved in the coordination of collective movements in groups of organisms. We then apply this method to characterize social interactions in two species of shoaling fish, the rummy-nose tetra (Hemigrammus rhodostomus) and the zebrafish (Danio rerio), which both present a burst-and-coast motion. From the detailed quantitative description of individual-level interactions, it is thus possible to develop a quantitative model of the emergent dynamics observed at the group level, whose predictions can be checked against experimental results. This method can be applied to a wide range of biological and social systems.

2020

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

Frank Bonnet, Bertrand Eric Collignon, Francesco Mondada, Vaios Papaspyros

Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed groups of sensor-rich robots and animals and study collective interactions from the within a bio-hybrid group. In recent work, scientists showed that a robot-controlled lure is capable of influencing the collective decisions of zebrafish Danio rerio shoals moving in a ring and a two-room setup. Here, we study a closely related topic, that is, the collective behavior patterns that emerge when different behavioral models are reproduced through the use of a robotic lure. We design a behavioral model that alternates between obeying and disobeying the collective motion decisions in order to become socially accepted by the shoal members. Subsequently, we compare it against two extreme cases: a reactive and an imposing decision model. For this, we use spatial, directional and information theoretic metrics to measure the degree of integration of the robotic agent. We show that our model leads to similar information flow as in freely roaming shoals of zebrafish and exhibits leadership skills more often than the open-loop models. Thus, in order for the robot to achieve higher degrees of integration in the zebrafish shoal, it must, like any other shoal member, be bidirectionally involved in the decision making process. These findings provide insight on the ability to form mixed societies of animals and robots and yield promising results on the degree to which a robot can influence the collective decision making.

2019