A future of living machines? International trends and prospects in biomimetic and biohybrid systems

Research in the fields of biomimetic and biohybrid systems is developing at an accelerating rate. Biomimetics can be understood as the development of new technologies using principles abstracted from the study of biological systems, however, biomimetics can also be viewed from an alternate perspective as an important methodology for improving our understanding of the world we live in and of ourselves as biological organisms. A biohybrid entity comprises at least one artificial (engineered) component combined with a biological one. With technologies such as microscale mobile computing, prosthetics and implants, humankind is moving towards a more biohybrid future in which biomimetics helps us to engineer biocompatible technologies. This paper reviews recent progress in the development of biomimetic and biohybrid systems focusing particularly on technologies that emulate living organisms—living machines. Based on our recent bibliographic analysis [1] we examine how biomimetics is already creating life-like robots and identify some key unresolved challenges that constitute bottlenecks for the field. Drawing on our recent research in biomimetic mammalian robots, including humanoids, we review the future prospects for such machines and consider some of their likely impacts on society, including the existential risk of creating artifacts with significant autonomy that could come to match or exceed humankind in intelligence. We conclude that living machines are more likely to be a benefit than a threat but that we should also ensure that progress in biomimetics and biohybrid systems is made with broad societal consent. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only

Growing-up hand in hand with robots: Designing and evaluating child-robot interaction from a developmental perspective

Robots are becoming part of children's care, entertainment, education, social assistance and therapy. A steadily growing body of Human-Robot Interaction (HRI) research shows that child-robot interaction (CRI) holds promises to support children's development in novel ways. However, research has shown that technologies that do not take into account children's needs, abilities, interests, and developmental characteristics may have a limited or even negative impact on their physical, cognitive, social, emotional, and moral development. As a result, robotic technology that aims to support children via means of social interaction has to take the developmental perspective into consideration. With this workshop (the third of a series of workshops focusing CRI research), we aim to bring together researchers to discuss how a developmental perspective play a role for smart and natural interaction between robots and children. We invite participants to share their experiences on the challenges of taking the developmental perspective in CRI, such as long-term sustained interactions in the wild, involving children and other stakeholders in the design process and more. Looking across disciplinary boundaries, we hope to stimulate thought-provoking discussions on epistemology, methods, approaches, techniques, interaction scenarios and design principles focused on supporting children's development through interaction with robotic technology. Our goal does not only focus on the conception and formulation of the outcomes in the context of the workshop venue, but also on their establishment and availability for the HRI community in different forms

Feed-Forward Chains of Recurrent Attractor Neural Networks Near Saturation

We perform a stationary state replica analysis for a layered network of Ising spin neurons, with recurrent Hebbian interactions within each layer, in combination with strictly feed-forward Hebbian interactions between successive layers. This model interpolates between the fully recurrent and symmetric attractor network studied by Amit el al, and the strictly feed-forward attractor network studied by Domany et al. Due to the absence of detailed balance, it is as yet solvable only in the zero temperature limit. The built-in competition between two qualitatively different modes of operation, feed-forward (ergodic within layers) versus recurrent (non- ergodic within layers), is found to induce interesting phase transitions.Comment: 14 pages LaTex with 4 postscript figures submitted to J. Phys.

A sensing architecture for empathetic data systems

Today's increasingly large and complex databases require novel and machine aided ways of exploring data. To optimize the selection and presentation of data, we suggest an unconventional approach. Instead of exclusively relying on explicit user input to specify relevant information or to navigate through a data space, we exploit the power and potential of the users' unconscious processes in addition. To this end, the user is immersed in a mixed reality environment while his bodily reactions are captured using unobtrusive wearable devices. The users' reactions are analyzed in real-time and mapped onto higher-level psychological states, such as surprise or boredom, in order to trigger appropriate system responses that direct the users' attention to areas of potential interest in the visualizations. The realization of such a close experience-based human-machine loop raises a number of technical challenges, such as the real-time interpretation of psychological user states. The paper at hand describes a sensing architecture for empathetic data systems that has been developed as part of such a loop and how it tackles the diverse challenges

Epigenetic editing:towards realization of the curable genome concept

Recent developments in biotechnology have enabled scientists to modulate DNA sequences in a precise way. These genome engineering technologies also open new possibilities to alter the epigenetic composition of the genome at any given genomic location thereby changing gene expression patterns, while leaving the primary DNA sequence intact. This new approach, so-called epigenetic editing, holds great promise to permanently reprogram cell identity. As reprogramming the epigenetic composition, and hence gene expression patterns is now technically feasible, the society needs to consider to what extent interference at the epigenetic level can be accepted. In this review, we discuss the potential epigenetic editing holds for research and therapy, and also touch upon societal implications of this rapidly growing research field

Towards a synthetic tutor assistant: The EASEL project and its architecture

Robots are gradually but steadily being introduced in our daily lives. A paramount application is that of education, where robots can assume the role of a tutor, a peer or simply a tool to help learners in a specific knowledge domain. Such endeavor posits specific challenges: affective social behavior, proper modelling of the learner’s progress, discrimination of the learner’s utterances, expressions and mental states, which, in turn, require an integrated architecture combining perception, cognition and action. In this paper we present an attempt to improve the current state of robots in the educational domain by introducing the EASEL EU project. Specifically, we introduce the EASEL’s unified robot architecture, an innovative Synthetic Tutor Assistant (STA) whose goal is to interactively guide learners in a science-based learning paradigm, allowing us to achieve such rich multimodal interactions

Complex network changes during a virtual reality rehabilitation protocol following stroke: a case study

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORStroke is one of the main causes of disabilities caused by injuries to the human central nervous system, yielding a wide range of mild to severe impairments that can compromise sensorimotor and cognitive functions. Although rehabilitation protocols may improve function of stroke survivors, patients often reach plateaus while undergoing therapy. Recently, virtual reality (VR) technologies have been paired with traditional rehabilitation aiming to improve function recovery after stroke. Aiming to better understand structural brain changes due to VR rehabilitation protocols, we modeled the brain as a graph and extracted three measures representing the network's topology: degree, clustering coefficient and betweenness centrality (BC). In this single case study, our results indicate that all metrics increased on the ipsilesional hemisphere, while remaining about the same at the contralesional site. Particularly, the number of functional connections increased in the lesion area overtime. In addition, the BC displayed the highest variations, and in brain regions related to the patient's cognitive and motor impairments; hence, we argue that this measure could be regarded as an indicative for brain plasticity mechanisms.891894FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIOR2013/07559-3Sem informação9. IEEE/EMBS International Conference on Neural Engineering (NER)20 a 23 de Março de 2019San Francisco, CA, Estados UnidosIEEE; EMB