Adaptive foraging for simulated and real robotic swarms: The dynamical response threshold approach

Developing self-organised swarm systems capable of adapting to environmental changes as well as to dynamic situations is a complex challenge. An efficient labour division model, with the ability to regulate the distribution of work among swarm robots, is an important element of this kind of system. This paper extends the popular response threshold model and proposes a new adaptive response threshold model (ARTM). Experiments were carried out in simulation and in real-robot scenarios with the aim of studying the performance of this new adaptive model. Results presented in this paper verify that the extended approach improves on the adaptability of previous systems. For example, by reducing collision duration among robots in foraging missions, our approach helps small swarms of robots to adapt more efficiently to changing environments, thus increasing their self-sustainability (survival rate). Finally, we propose a minimal version of ARTM, which is derived from the conclusions drawn through real-robot and simulation results

Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perceptionThis study was supported by the European Commission with the RoboSoft CA (A Coordination Action for Soft Robotics, contract #619319). SGN was supported by School of Engineering seed funding (2016), Malaysia Campus, Monash University

Identifying the Evolutionary Conditions for the Emergence of Alternative Reproductive Tactics in Simulated Robot Colonies

Alternative reproductive tactics (ARTs), phenomena in which individuals within one sex adopt different tactics for accessing mates or raising offspring, are commonly observed in all major taxa. In order to study the ecological conditions for the emergence of ARTs, we developed an embodied evolution framework incorporating ecological features, such as body size and energy maintenance, where male and female robotic agents naturally face both intersexual and intrasexual interactions for survival and reproduction. Each agent has a decision neural network with extrinsic and intrinsic sensory inputs to choose one of four basic behaviors: mating, foraging, approaching and waiting. The reproductive success depends on the body size and the energy level of both male and female upon mating and it is assumed that only female carries the reproduction cost, as in nature the cost of male’s sperm production is negligible relative to that of female’s eggs. We performed simulation experiments in environments with different conditions (food density, reproductive cost, and male-female ratio) and found ARTs emerged both in males and females. Males evolved three kinds of alternative tactics - fixed genetically distinct ARTs (dominant and sneaker males that differ in body size and the tactic for getting access to female), conditionally flexible ARTs (individuals change tactics according to body size), and mixed ARTs (combination of genetically fixed and conditionally flexible ARTs). Females evolved to have two genetically distinct ARTs (quality oriented female, QoF, and number oriented female, NoF), where they increase fitness either by offspring quality or quantity. Analysis of the results confirms the experimental notions that male genetically fixed ARTs are strongly affected by intensity of sexual selection, male conditionally flexible ARTs are significantly affected by competition level, and female ARTs are mainly affected by food density. Analysis of ESS shows male ARTs are evolutionary stable with negative frequency dependent selection and female ARTs are evolutionary stable with both frequency and density dependent selection. To our knowledge, this study is the first to show the emergence of ARTs in both male and female from initially continuous characteristics in a simulated embodied evolution framework. The evolved ARTs are quite similar to the ARTs found in nature and provide insights about how interactions between the sexes are affected by and affect the evolution of ARTs within each sex. This framework is flexible enough to further analyze species of different sexual mechanisms (hermaphrodite, androdioecious, gynodioecious, etc.) and can be used as an important tool to understand the ecology of social interaction.Okinawa Institute of Science and Technology Graduate Universit

Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

Visual homing in field crickets and desert ants: a comparative behavioural and modelling study

Visually guided navigation represents a long standing goal in robotics. Insights may be drawn from various insect species for which visual information has been shown sufficient for navigation in complex environments, however the generality of visual homing abilities across insect species remains unclear. Furthermore variousmodels have been proposed as strategies employed by navigating insects yet comparative studies across models and species are lacking. This work addresses these questions in two insect species not previously studied: the field cricket Gryllus bimaculatus for which almost no navigational data is available; and the European desert ant Cataglyphis velox, a relation of the African desert ant Cataglyphis bicolor which has become a model species for insect navigation studies. The ability of crickets to return to a hidden target using surrounding visual cues was tested using an analogue of the Morris water-maze, a standard paradigm for spatial memory testing in rodents. Crickets learned to re-locate the hidden target using the provided visual cues, with the best performance recorded when a natural image was provided as stimulus rather than clearly identifiable landmarks. The role of vision in navigation was also observed for desert ants within their natural habitat. Foraging ants formed individual, idiosyncratic, visually guided routes through their cluttered surroundings as has been reported in other ant species inhabiting similar environments. In the absence of other cues ants recalled their route even when displaced along their path indicating that ants recall previously visited places rather than a sequence of manoeuvres. Image databases were collected within the environments experienced by the insects using custompanoramic cameras that approximated the insect eye viewof the world. Six biologically plausible visual homing models were implemented and their performance assessed across experimental conditions. The models were first assessed on their ability to replicate the relative performance across the various visual surrounds in which crickets were tested. That is, best performance was sought with the natural scene, followed by blank walls and then the distinct landmarks. Only two models were able to reproduce the pattern of results observed in crickets: pixel-wise image difference with RunDown and the centre of mass average landmark vector. The efficacy of models was then assessed across locations in the ant habitat. A 3D world was generated from the captured images providing noise free and high spatial resolution images asmodel input. Best performancewas found for optic flow and image difference based models. However in many locations the centre of mass average landmark vector failed to provide reliable guidance. This work shows that two previously unstudied insect species can navigate using surrounding visual cues alone. Moreover six biologically plausible models of visual navigation were assessed in the same environments as the insects and only an image difference based model succeeded in all experimental conditions

Perception in real and artificial insects: a robotic investigation of cricket phonotaxis

The aim of this thesis is to investigate a methodology for studying percep¬ tual systems by building artificial ones. It is proposed that useful results can be obtained from detailed robotic modelling of specific sensorimotor mechanisms in lower animals. By looking at the sensory control of behaviour in simple biological organisms, and in working robots, it is argued that proper appreciation of the physical interaction of the system with the environment and the task is essential for discovering how perceptual mechanisms function. Although links to biology, and concern with perceptual competence, are fields of growing interest in Artificial Intelligence, much of the current research fails to adequately address these issues, as the model systems being built do not represent real sensorimotor problems.By analyzing what is required for a model of a system to contribute to ex¬ plaining that system, a particular approach to modeling perceptual systems is suggested. This involves choosing an appropriate target system to model, building a system that validly represents the target with respect to a particular hypothesis, and properly evaluating the behaviour of the model system to draw conclusions about the target. The viability and potential contribution of this approach is demonstrated in the design, implementation and evaluation of a mobile robot model of a hypothesised mechanism for phonotaxis in the cricket.The result is a robot that successfully locates a specific sound source under a variety of conditions, with a range of behaviour that resembles the cricket in many ways. This provides some support for the hypothesis that the neural mechanism for phonotaxis in crickets does not involve separate processing for recognition and location of the signal, as is generally supposed. It also shows the importance of un¬ derstanding the physical interaction of the system's structure with its environment in devising and implementing perceptual systems. Both these results vindicate the proposed methodology

Neural dynamics of social behavior : An evolutionary and mechanistic perspective on communication, cooperation, and competition among situated agents

Social behavior can be found on almost every level of life, ranging from microorganisms to human societies. However, explaining the evolutionary emergence of cooperation, communication, or competition still challenges modern biology. The most common approaches to this problem are based on game-theoretic models. The problem is that these models often assume fixed and limited rules and actions that individual agents can choose from, which excludes the dynamical nature of the mechanisms that underlie the behavior of living systems. So far, there exists a lack of convincing modeling approaches to investigate the emergence of social behavior from a mechanistic and evolutionary perspective. Instead of studying animals, the methodology employed in this thesis combines several aspects from alternative approaches to study behavior in a rather novel way. Robotic models are considered as individual agents which are controlled by recurrent neural networks representing non-linear dynamical system. The topology and parameters of these networks are evolved following an open-ended evolution approach, that is, individuals are not evaluated on high-level goals or optimized for specific functions. Instead, agents compete for limited resources to enhance their chance of survival. Further, there is no restriction with respect to how individuals interact with their environment or with each other. As its main objective, this thesis aims at a complementary approach for studying not only the evolution, but also the mechanisms of basic forms of communication. For this purpose it can be shown that a robot does not necessarily have to be as complex as a human, not even as complex as a bacterium. The strength of this approach is that it deals with rather simple, yet complete and situated systems, facing similar real world problems as animals do, such as sensory noise or dynamically changing environments. The experimental part of this thesis is substantiated in a five-part examination. First, self-organized aggregation patterns are discussed. Second, the advantages of evolving decentralized control with respect to behavioral robustness and flexibility is demonstrated. Third, it is shown that only minimalistic local acoustic communication is required to coordinate the behavior of large groups. This is followed by investigations of the evolutionary emergence of communication. Finally, it is shown how already evolved communicative behavior changes during further evolution when a population is confronted with competition about limited environmental resources. All presented experiments entail thorough analysis of the dynamical mechanisms that underlie evolved communication systems, which has not been done so far in the context of cooperative behavior. This framework leads to a better understanding of the relation between intrinsic neurodynamics and observable agent-environment interactions. The results discussed here provide a new perspective on the evolution of cooperation because they deal with aspects largely neglected in traditional approaches, aspects such as embodiment, situatedness, and the dynamical nature of the mechanisms that underlie behavior. For the first time, it can be demonstrated how noise influences specific signaling strategies and that versatile dynamics of very small-scale neural networks embedded in sensory-motor feedback loops give rise to sophisticated forms of communication such as signal coordination, cooperative intraspecific communication, and, most intriguingly, aggressive interspecific signaling. Further, the results demonstrate the development of counteractive niche construction based on a modification of communication strategies which generates an evolutionary feedback resulting in an active reduction of selection pressure, which has not been shown so far. Thus, the novel findings presented here strongly support the complementary nature of robotic experiments to study the evolution and mechanisms of communication and cooperation.</p