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17th Genetic and evolutionary Computation Conference (GECCO)

作者： Soorati, Mohammad Divband Hamann, Heiko Univ Paderborn Dept Comp Sci D-33102 Paderborn Germany

ISBN: (纸本)9781450334723

Fitness function design is known to be a critical feature of the evolutionary-robotics approach. Potentially, the complexity of evolving a successful controller for a given task can be reduced by integrating a priori knowledge into the fitness function which complicates the comparability of studies in evolutionary robotics. Still, there are only few publications that study the actual effects of different fitness functions on the robot's performance. In this paper, we follow the fitness function classification of Nelson et al. (2009) and investigate a selection of four classes of fitness functions that require different degrees of a priori knowledge. The robot controllers are evolved in simulation using NEAT and we investigate different tasks including obstacle avoidance and (periodic) goal homing. The best evolved controllers were then post-evaluated by examining their potential for adaptation, determining their convergence rates, and using cross-comparisons based on the different fitness function classes. The results confirm that the integration of more a priori knowledge can simplify a task and show that more attention should be paid to fitness function classes when comparing different studies.

关键词： evolutionary robotics fitness function design

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Combining Conflicting Environmental and Task Requirements in evolutionary robotics 9

Combining Conflicting Environmental and Task Requirements in...

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9th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO)

作者： Haasdijk, Evert Vrije Univ Amsterdam Dept Comp Sci Amsterdam Netherlands

ISBN: (纸本)9781467375351

The MONEE framework endows collective adaptive robotic systems with the ability to combine environment- and task-driven selection pressures: it enables distributed online algorithms for learning behaviours that ensure both survival and accomplishment of user-defined tasks. This paper explores the trade-off between these two requirements that evolution must establish when the task is detrimental to survival. To this end, we investigate experiments with populations of 100 simulated robots in a foraging task scenario where successfully collecting resources negatively impacts an individual's remaining lifetime. We find that the population remains effective at the task of collecting pucks even when the negative impact of collecting a puck is as bad as halving the remaining lifetime. A quantitative analysis of the selection pressures reveals that the task-based selection exerts a higher pressure than the environment.

关键词： robots MONEE framework collective adaptive robotic systems conflicting environmental requirement distributed online algorithms environment-driven selection pressure evolutionary robotics foraging task scenario learning behaviours quantitative analysis task requirement task-based selection task-driven selection pressure user-defined tasks Evolution (biology) Genomics Robot sensing systems Sociology Statistics Toxicology Embodied Evolution Environment-driven Evolution evolutionary robotics Manipulator sensing systems Sociology Robot QUANTITATIVE ANALYSIS Toxicology Genomics

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Unleashing the Potential of evolutionary Swarm robotics in the Real World

Unleashing the Potential of Evolutionary Swarm Robotics in t...

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Genetic and evolutionary Computation Conference (GECCO)

作者： Duarte, Miguel Costa, Vasco Gomes, Jorge Rodrigues, Tiago Silva, Fernando Oliveira, Sancho Moura Christensen, Anders Lyhne BioMachines Lab Lisbon Portugal Inst Telecomunicacoes Lisbon Portugal Inst Univ Lisboa ISCTE IUL Lisbon Portugal BioISI Fac Ciencias Lisbon Portugal

ISBN: (纸本)9781450343237

We provide a summary of our real-world experiments with a swarm of aquatic surface robots with evolved control. Robotic control was synthesized in simulation, using offline evolutionary robotics techniques, and then successfully transferred to a real swarm. Our study presents one of the first demonstrations of evolved control in a swarm robotics system outside of controlled laboratory conditions. Original publication: M. Duarte, V. Costa, J. Comes, T. Rodrigues, F. Silva, S. M. Oliveira, and A. L. Christensen. Evolution of collective behaviors for a real swarm of aquatic surface robots. PLoS ONE, 11(3):e0151834, 2016.

关键词： reality gap evolutionary robotics swarm robotics aquatic robots

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Assessing the Effect of Self-Assembly Ports in evolutionary Swarm robotics

Assessing the Effect of Self-Assembly Ports in Evolutionary ...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Ripon, Kazi Shah Nawaz Jakobsen, Eirik Tannum, Christopher Montanier, Jean-Marc Norwegian Univ Sci & Technol Dept Comp & Informat Sci Trondheim Norway Protolab Softbank Robot Europe Paris France

ISBN: (纸本)9781509042401

Self-assembly in swarm robotics is essential for a group of robots in achieving a common goal that is not possible to achieve by a single robot. Self-assembly also provides several advantages to swarm robotics. Some of these include versatility, scalability, re-configurability, cost-effectiveness, extended reliability, and capability for emergent phenomena. This work investigates the effect of self-assembly in evolutionary swarm robotics. Because of the lack of research literature within this paradigm, there are few comparisons of the different implementations of self-assembly mechanisms. This paper reports the influence of connection port configuration on evolutionary self-assembling swarm robots. The port configuration consists of the number and the relative positioning of the connection ports on each of the robot. Experimental results suggest that configuration of the connection ports can significantly impact the emergence of self-assembly in evolutionary swarm robotics.

关键词： evolutionary robotics self-assembly machine learning connection port configuration docking mechanism

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Neuromodelling based on evolutionary robotics: On the importance of motor control for spatial attention

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COGNITIVE PROCESSING 2015年第1-Sup期16卷 S31-S32页

作者： Gigliotta, Onofrio Miglino, Orazio Bartolomeo, Paolo Univ Naples Federico II Naples Italy ISTC CNR Rome Italy UPMC Hop Salpetriere Brain & Spine Inst INSERMUMRS Paris France

Mainstream approaches to modelling cognitive processes have typically focused on (1) reproducing their neural underpinning, without regard to sensory-motor systems and (2) producing a single, ideal computational model. evolutionary robotics is an alternative possibility to bridge the gap between neural substrate and behavior by means of a sensory-motor apparatus, and a powerful tool to build a population of individuals rather than a single model. We trained 4 populations of neurorobots, equipped with a pan/tilt/zoom camera, and provided with different types of motor control in order to perform a cancellation task, often used to tap spatial cognition. Neurorobots’ eye movements were controlled by (a) position, (b) velocity, (c) simulated muscles and (d) simulated muscles with fixed level of zoom. Neurorobots provided with muscle and velocity control showed better performances than those controlled in position. This is an interesting result since muscle control can be considered a particular type of position control. Finally, neurorobots provided with muscle control and zoom outperformed those without zooming ability.

关键词： Simulation Cancellation task Neural networks Neurorobots evolutionary robotics

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Elements of embodied evolutionary robotics 15

Elements of embodied evolutionary robotics

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17th Genetic and evolutionary Computation Conference, GECCO 2015

作者： Bredeche, Nicolas Haasdijk, Evert Prieto, Abraham Sorbonne Universités UPMC Univ Paris 06 UMR 7222 ISIR ParisF-75005 France CNRS UMR 7222 ISIR ParisF-75005 France VU University Amsterdam Amsterdam Netherlands Integrated Group for Engineering Research Universidade da Coruña Spain

This workshop presentation describes the general concepts behind embodied evolution, and intends to provide an up-to-date view of lessons learned and current open issues.

ISBN: (纸本)9781450334884

This workshop presentation describes the general concepts behind embodied evolution, and intends to provide an up-to-date view of lessons learned and current open issues.

关键词： evolutionary robotics embodied evolution

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evolutionary robotics

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COMMUNICATIONS OF THE ACM 2013年第8期56卷 74-83页

作者： Bongard, Josh C. Univ Vermont Dept Comp Sci Evolut & Cognit Lab Burlington VT 05405 USA

Taking a biologically inspired approach to the design of autonomous, adaptive machines.

关键词： Artificial intelligence Algorithms evolutionary robotics Autonomous robots robotics research Dynamical systems

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Recent advances in evolutionary and bio-inspired adaptive robotics: Exploiting embodied dynamics

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APPLIED INTELLIGENCE 2021年第9期51卷 6467-6496页

作者： Husbands, Phil Shim, Yoonsik Garvie, Michael Dewar, Alex Domcsek, Norbert Graham, Paul Knight, James Nowotny, Thomas Philippides, Andrew Univ Sussex Dept Informat Ctr Computat Neurosci & Robot Brighton E Sussex England Pai Chai Univ Dept Game & Multimedia Engn Daejeon South Korea Univ Sussex Dept Informat CCNR Brighton E Sussex England Univ Sussex Sch Life Sci CCNR Brighton E Sussex England

This paper explores current developments in evolutionary and bio-inspired approaches to autonomous robotics, concentrating on research from our group at the University of Sussex. These developments are discussed in the context of advances in the wider fields of adaptive and evolutionary approaches to AI and robotics, focusing on the exploitation of embodied dynamics to create behaviour. Four case studies highlight various aspects of such exploitation. The first exploits the dynamical properties of a physical electronic substrate, demonstrating for the first time how component-level analog electronic circuits can be evolved directly in hardware to act as robot controllers. The second develops novel, effective and highly parsimonious navigation methods inspired by the way insects exploit the embodied dynamics of innate behaviours. Combining biological experiments with robotic modeling, it is shown how rapid route learning can be achieved with the aid of navigation-specific visual information that is provided and exploited by the innate behaviours. The third study focuses on the exploitation of neuromechanical chaos in the generation of robust motor behaviours. It is demonstrated how chaotic dynamics can be exploited to power a goal-driven search for desired motor behaviours in embodied systems using a particular control architecture based around neural oscillators. The dynamics are shown to be chaotic at all levels in the system, from the neural to the embodied mechanical. The final study explores the exploitation of the dynamics of brain-body-environment interactions for efficient, agile flapping winged flight. It is shown how a multi-objective evolutionary algorithm can be used to evolved dynamical neural controllers for a simulated flapping wing robot with feathered wings. Results demonstrate robust, stable, agile flight is achieved in the face of random wind gusts by exploiting complex asymmetric dynamics partly enabled by continually changing wing and tail morpho

关键词： evolutionary robotics Biorobotics Visual navigation Neural dynamics Chaotic dynamics Evolvable hardware

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Assessing the Effect of Self-Assembly Ports in evolutionary Swarm robotics

Assessing the Effect of Self-Assembly Ports in Evolutionary ...

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IEEE Symposium Series on Computational Intelligence

作者： Kazi Shah Nawaz Ripon Eirik Jakobsen Christopher Tannum Jean-Marc Montanier Department of Computer and Information Science Norwegian University of Science and Technology Norway protolab - Softbank Robotics Europe

ISBN: (纸本)9781509042418

关键词： evolutionary robotics self-assembly machine learning connection port configuration docking mechanism

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An evolutionary robotics approach for the distributed control of satellite formations

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evolutionary INTELLIGENCE 2014年第2期7卷 107-118页

作者： Izzo, Dario Simoes, Luis F. de Croon, Guido C. H. E. European Space Agcy Adv Concepts Team Noordwijk Netherlands Vrije Univ Amsterdam Computat Intelligence Grp Amsterdam Netherlands Delft Univ Technol Micro Air Vehicle Lab Delft Netherlands

We propose and study a decentralized formation flying control architecture based on the evolutionary robotic technique. We develop our control architecture for the MIT SPHERES robotic platform on board the International Space Station and we show how it is able to achieve micrometre and microradians precision at the path planning level. Our controllers are homogeneous across satellites and do not make use of labels (i.e. all satellites can be exchanged at any time). The evolutionary process is able to produce homogeneous controllers able to plan, with high precision, for the acquisition and maintenance of any triangular formation.

关键词： Satellite swarm control evolutionary robotics Neural networks Particle swarm optimization

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