226 research outputs found
Embodied Evolutionary Robotics with Large Number of Robots
No full textEmbodied evolutionary robotics is a particular flavour of evo-lutionary robotics, where the evolutionary optimization of behaviours is achieved in an on-line and distributed fash-ion (Watson et al., 2002). The question asked in this paper is: does population size play a role in the evolution of partic-ular behaviours? We experimentaly demonstrate that varying the number of robots and the size of the environment can lead to very different outcomes in terms of evolved behaviours. Figure 1: Experimental setup: a population of robots with 8 infra-red (IR) sensors (shown in blue) is deployed in an envi-ronment where 10 (yellow) landmarks are randomly placed. The robots are modelled after the famous e-puck robot, and communication between robots is achieved through the IR devices. The red tail is visible to the user only (used fo
Designing Self-Organization in the Physical Realm
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
Online Learning for Object Identification By a Mobile Robot
No full textObject identification for a situated robot is a first step towards many relevant behaviours such as human-robot communication, object tracking, object detection, etc. However, the dynamic and unpredictable nature of the world makes it very di#cult to design such algorithms. Our goal is to endow a Pioneer 2DX autonomous mobile robot with the ability to learn how to identify objects from its environment, and to maintain this ability through time. In order to do so, we propose an architecture that continuously looks for relevant visual invariant properties related to target objects thanks to online learning techniques
Designing Self-Organization in the Physical Realm
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
A Multi-Cellular Developmental System in Continuous Space using Cell Migration
No full textInternational audienceThis paper introduces a novel multi-cellular developmental system where cells are placed in a continuous space. Cells communicate by diffusing and perceiving substances in the environment and are able to migrate around following affinities with substance gradients. The optimization process is performed using Echo State neural networks on the problem of minimizing tile size variations in the context of a tiling problem. Experimental results show that problem complexity only impacts the number of substances used, rather than the number of cells, which implies some sort of scalability with regards to the size of the phenotype. Symmetry breaking and robustness are addressed by adding noise as an intrinsic property of the model. A (positive) side effect is that the resulting model produces very robust solutions with efficient self-healing behavior in the presence of perturbations never met before
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