For biohybrid systems involving robot interactions with a large and varied population of animals, it could be beneficial to deploy a morphologically and behaviorally varied population of robots into the environment, for successful interactions across the full diversity of the relevant biological population. In this paper, we briefly summarize our work in two areas integral to this effort: (1) computational investigations of bioinspired methods for retaining population-level variance under evolution; and (2) quantitative evolutionary analysis of genetics and morphology. We also consider ideas for Cognitive Science-inspired work in designing goal-directed behaviors for the robots in biohybrid systems. Based on the underlying idea that robot designs with deeper roots in biology can result in more effective biohybrid systems, our perspectives and approaches could illuminate new commonalities between evolved robot populations and evolved biological populations, which would ideally improve the robots as tools for scientific insight into animals, their behaviors, and their environments.

Recent progress in “artificial” (or “synthetic”) cell research has allowed the construction of sophisticated systems capable of sending/receiving chemical signals to/from biological cells. This new scenario paves the way to conceptually new technologies and scientific investigations based on interfacing organisms (natural cells) and robots (artificial cells) and exploiting their built-in molecular communication capacity. The state-of-the-art is presented and commented from the perspective of Artificial Life and synthetic biology.

In the wake of climate change and water quality crisis, it is crucial to find novel ways to extensively monitor the environment and to detect ecological changes early. Biomonitoring has been found to be an effective way of observing the aggregate effect of environmental fluctuations. In this paper, we outline the development of biohybrids which will autonomously observe simple organisms (microorganisms, algae, mussels etc.) and draw conclusions about the state of the water body. These biohybrids will be used for continuous environmental monitoring and to detect sudden (anthropologically or ecologically catastrophic) events at an early stage. Our biohybrids are being developed within the framework of project Robocoenosis, where the operational area planned are Austrian lakes. Additionally, we discuss the possible use of various species found in these waters and strategies for biomonitoring. We present early prototypes of devices that are being developed for monitoring of organisms.

Robotics is emerging as a promising approach to study animal behavior. Biologically-inspired robots can manipulate the behavior of live animals and are increasingly employed to uncover the underpinnings of sociality and mate choice in the animal realm. But behavioral variation between animals plays a critical role for their ecology and evolution, and ultimately it determines variation in the survival, growth, and reproduction of individuals. While the study of behavioral responses of animals toward their robotic counterparts dominates the literature, it remains largely untested whether the life-history strategies of live animals can be artificially manipulated with biologically-inspired robots. Recently, predator-mimicking robots allowed to successfully study antipredator responses of highly invasive fish in detail, revealing that costs of behavioral alternations induced by robotic predators can impact the health and survival of invaders. The evidence that biologically-inspired robots can undermine the ecological success of invasive animals opens the door to novel experimental analyses at the interface between robotics, ecology, and invasion biology.

We used a model of honeybees’ decision-making to investigate the effect of robots on the hive's foraging decisions. We find that at least two robots are needed to make a significant impact.

In a time marked by ecological decay and by the perspective of a severe backlash of this ecosystem decay and climate devastation onto human society, bold moves that employ novel technology to counteract this decline are required. We present a novel concept of employing Artificial Life technology, in the form of cybernetically enhanced bio-hybrid superorganisms as a countermeasure and as a contingency plan. We describe our general conceptual paradigm, consisting of three interacting action plans, namely: (1) Organismic Augmentation; (2) Bio- Hybrid Socialization and (3) Ecosystem Hacking, which together compose a method to create a novel agent for ecosystem stabilization. We demonstrate, through early results from the research project HIVEOPOLIS, a specific way how classic Artificial Life technologies can create such a living, ecologically active and technologically-augmented superorganism that operates outside in the field. These technologies range from cellular automata and biomimetic robots to novel and sustainable biocompatible materials. Aiming at having a real-world impact on the society that relies on our biosphere is an important aspect in Artificial Life research and is fundamental to our methodology to create a physically embodied and useful form of Artificial Life.

Lures and artefacts, which are almost as old as hunting and fishing, are used to elicit a particular behaviour in animals through key signals. The advances in robotics and sensors/actuators technologies opened the way to go from passive decoys to decoys able to fully interact with animals. Of special interest in this context are social species that are characterized by large networks of feedbacks of similar types but that involve various physicochemical vectors. The monitoring, the control and the breeding/farming of such populations often involve changes to the environment including artefacts that can be seen as environmental decoys. In this paper, we take the paradigmatic case of the formation of aggregates in a patchy environment : gregarious individuals having the choice to settle under an arbitrary number of shelters that are artificial agents able to communicate between themselves and to interact with the sheltered individuals through the modification of their abiotic factors such as temperature, light or odour. These systems can be modelled by the same generic models that serve as prediction and management tools. The model analysis allows to identify the behaviour of the artificial agents/shelters optimizing the population management.

Animals that live in social groups must interact in order to stay together and move collectively. By socializing a robot with a group of weakly electric fish, we aim at answering fundamental biological questions about the rules that govern social interactions and cause group members to coordinate their movements and come to joint decisions. African weakly electric fish communicate at night by emitting and perceiving short electrical current pulses, a process called electro-communication. Our experiments have shown that it is only possible to integrate a robotic agent into a group of electric fish if it emits electric signals and engages in electro-communication. All other sensory cues, like visual appearance, can be neglected. For full acceptance as a conspecific by live fish, the robot must be able to interact with the animals. We hypothesize that the integration of fish and robot into a mixed society can succeed when the robot's electric signaling interaction is matched by locomotor interactions that are congruent with the behavioral relevance of electro-communication.

In order to strengthen animal welfare, many countries require that experimenters follow the ‘3Rs Principle’ when designing animal experiments. The 3Rs call for a reduction in the number of animals used, the refinement of methods to reduce stress as well as the full replacement of animals in experimentation through alternative methods. Biomimetic robots that resemble live animals and allow for natural-like interactions represent a valuable tool to achieve the 3Rs’ objectives. On the basis of our research with a robotic fish that is accepted as a conspecific by live poeciliid fishes, we highlight how biomimetic robots can reduce the number of animals tested by (a) substituting live animals, (b) providing highly standardized cues, and (c) reducing overall stress for live animals during tests through less handling.

In the Star Trek universe, Scotty can ”beam you up” and teleport you to a location. Even though science fiction is yet to be reality, is teleporting still possible? Recently, we have developed a robotic platform that is capable of teleporting the behavior of fish from one tank to another through biologically-inspired robotic replicas which map the behavior of a fish from a tank to the other one. Our results indicate that behavioral teleporting is a promising tool to study the biological determinants of behavior. Here we demonstrate its use in pharmacological research, by investigating the effects of selective serotonin reuptake inhibitors of social interactions.

To investigate the sensitivity of a mixed fish-robot population to parameters governing the stochastic motion of a robotic constituent, this paper explores a robot motion model structure that facilitates the exploration of naturalistic changes in robot activity level. This model is intended for use in experiments involving interactions between a robot and a single Banded Archerfish (T. jaculatrix ). The robot motion framework consists of a two-state Markov chain coupled with an autoregressive motion model. The parameters governing the robot's motion are tuned to match those of actual individual archerfish, and can be manipulated to change robot activity level. This framework is being used in ongoing experiments designed to investigate the influence of robot activity level on an archerfish's behavioral response to the robot.

Growing cities are a world-wide phenomenon and simultaneously awareness about potential dangers due to air pollution, heat, and pathogens is increasing. Integrated and permanent monitoring of environmental features in cities can help to establish an early warning system and to provide data for policy makers. In our new project ‘WatchPlant,’ we propose a green approach for urban monitoring by a network of sensors tightly coupled with natural plants. We want to develop a sustainable, energy-efficient bio-hybrid system that harvests energy from living plants and utilizes methods of phytosensing, that is, using natural plants as sensors. We present our concept, here with focus on Alife-related methods operating on the gathered plant data and the bio-hybrid network. With a self-organizing network of sensors, that are alive, we hope to contribute to our future of livable green cities.

Biorobotics is a form of ‘hard’ Artificial Life research, as it involves experimentation on robotic models of living organisms. Rational justification of biorobotic experiments requires a careful analysis of their methodological structure. Philosophy of science has much to offer for this purpose. Here it is suggested that interactive branches of biorobotics adopt a methodology which radically departs from the “understanding by building” approach as traditionally conceived. It is also observed that some biorobotic studies aim neither at explaining nor at predicting phenomena, but at creating them in Hacking's sense. Finally, it is suggested that biorobotic studies vary in their scope, some of them being limited to the analysis of animal-robot interaction, others reaching conclusion on animal-animal interaction. These considerations are brought to bear on the complexities involved in the justification of biorobotics.

Biorobotics aims at developing artifacts as synthesis and simulation of living systems. Herein, an autonomous agent inspired to Lampetra fluviatilis that was developed in the framework of the LAMPETRA Project, has been described. Lampreys are established models for studying higher vertebrate locomotion, including humans. The LAMPETRA robotic artifact mimicked the flexibility, as well as the passive dynamic movement of the real animal, thanks to the muscle-like actuation system relying on the use of direct magnet interaction, and closely mimicking the central pattern generators (CPGs) architecture of the animal spinal cord. Furthermore, the robot included a binocular vision system to track objects and avoid obstacles, as well as an artificial skin that made it waterproof and compliant. This biomimetic agent can be used to interact with abiotic and biotic components of aquatic ecosystems, as well as could be interfaced with the central nervous systems of real fish creating a biohybrid configuration.

Underwater communication is a challenging issue for underwater robotics. This is especially the case for swarm robotics in confined spaces and turbid waters where neither sonar nor light can be used. This paper presents a new perspective for addressing this issue. The approach is based on artificial electric sense, a sensing ability inspired from weakly electric fish that can perceive their surroundings and communicate within a group by interpreting the electric fields generated by themselves or by conspecifics. This concept is implemented on a heterogenous swarm of underwater robots, named subCULTron, which is able to cooperate in order to explore and monitor its environment in the harsh conditions of the Venice Laguna.

Fish collective behaviours provide several benefits to conspecific individuals, although mixed-species aggregations have been reported to often occur. However, the mechanisms promoting phenotypically heterogeneous fish aggregations have been poorly explored so far. Herein, the neon tetra Paracheirodon innesi was selected as ideal model organism to test the role of visible phenotypic traits in promoting fish shoaling. Robotic fish replicas of different colour (e.g. biomimetic livery, blue livery, red livery, grey livery), but with the morphology inspired to P. innesi , were developed to test the affiliation behaviour of neon tetra individuals towards fish replicas with different phenotypic traits. P. innesi individuals showed a decreasing preference in shoaling with the biomimetic replica, the blue replica, the red replica and the grey replica. This could be due to the greater visibility of the blue colour even in dark conditions in these fish. Furthermore, an increased reddening of the livery is often caused by physiological processes related to a non-optimal behavioural status. The time spent in shoaling with each fish replica was strongly influenced by different ecological contexts. The longest shoaling duration was observed when a biomimetic predator was present, while the shortest shoaling duration was recorded in presence of food. This confirms the hypothesis that heterogeneous shoals are promoted by the anti-predator benefits, and reduced by competition. Our animal-robot interaction study allowed to understand basic features of the behavioural ecology favouring heterogeneous aggregations in shoaling fish, as well as provided a novel paradigm, based on biohybridization, for the artificial life synthetic methods.

Robot-plant bio-hybrid systems are getting increasing attention due to the wide range of applications they offer. Such synergies between robots and natural plants will allow, for example, establishing highly reliable environmental monitoring systems or growing the architecture of our future cities. We explore the latter application where robots exploit the plants’ ability to produce construction material, and plants exploit the robots’ sensing and computational capabilities. In our previous work, we used machine learning techniques to model plant behavior in their early life stages. We collected a 10-point plant stem description dataset and used it to train an LSTM as a forward model that predicts plant dynamics and drives the evolution of plant shaping controllers. Here, we show our vision to model plant behaviors in later stages, where full-plant morphology will be used to train state-of-the-art sequence modeling networks capable of simulating more complex plant dynamics.