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Open Issues in evolutionary robotics

evolutionary COMPUTATION 2016年第2期24卷 205-236页

作者： Silva, Fernando Duarte, Miguel Correia, Luis Oliveira, Sancho Moura Christensen, Anders Lyhne Bioinspired Computat & Intelligent Machines Lab P-1649026 Lisbon Portugal Univ Lisbon BioISI Fac Ciencias P-1749016 Lisbon Portugal Inst Telecomunicacoes P-1049001 Lisbon Portugal Inst Univ Lisboa ISCTE IUL P-1649026 Lisbon Portugal

One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versusevolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1)the bootstrap problem, (2)deception, and (3)the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

关键词： evolutionary robotics autonomous robots controller synthesis reality gap online evolution bootstrap problem deception genomic encoding research practices

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Concurrent controller and Simulator Neural Network development for a differentially-steered robot in evolutionary robotics

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robotics AND AUTONOMOUS SYSTEMS 2016年 76卷 80-92页

作者： Woodford, Grant W. Pretorius, Christiaan J. du Plessis, Mathys C. NMMU Dept Comp Sci Port Elizabeth South Africa NMMU Dept Math & Appl Math Port Elizabeth South Africa

evolutionary robotics (ER) strives for the automatic creation of robotic controllers and morphologies. The ER process is normally performed in simulation in order to reduce the time required and robot wear. Simulator development is a time consuming process which requires expert knowledge and must traditionally be completed before the ER process can commence. Traditional simulators have limited accuracy, can be computationally expensive and typically do not account for minor operational differences between physical robots. This research proposes the automatic creation of simulators concurrently with the normal ER process. The simulator is derived from an Artificial Neural Network (ANN) to remove the need for formulating an analytical model for the robot. The ANN simulator is improved concurrently with the ER process through real-world controller evaluations which continuously generate behavioural data. Simultaneously, the ER process is informed by the improving simulator to evolve better controllers which are periodically evaluated in the real-world. Hence, the concurrent processes provide further targeted behavioural data for simulator improvement. The concurrent and real-time creation of both controllers and ANN-based simulators is successfully demonstrated for a differentially-steered mobile robot. Various parameter settings in the proposed algorithm are investigated to determine factors pertinent to the success of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

关键词： evolutionary robotics Coevolution Simulator Artificial Neural Networks Differentially-Steered Mobile robotics

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An evolutionary robotics approach to a multi-legged robotic swarm in a rough terrain environment

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ARTIFICIAL LIFE AND robotics 2023年第4期28卷 661-668页

作者： Morimoto, Daichi Tsukamoto, Haruhi Hiraga, Motoaki Ohkura, Kazuhiro Munetomo, Masaharu Hiroshima Univ Hiroshima Japan Kyoto Inst Technol Kyoto Japan Hokkaido Univ Informat Initiat Ctr Sapporo Hokkaido Japan

This paper demonstrates a controller design of a multi-legged robotic swarm in a rough terrain environment. Many studies in swarm robotics are conducted with mobile robots that work in relatively flat fields. This paper focuses on a multi-legged robotic swarm, which is expected to operate not only in a flat field but also in rough terrain environments. However, designing a robot controller becomes a challenging problem because a designer has to consider how to coordinate a large number of joints in a robot, besides the complexity of a swarm problem. This paper employed an evolutionary robotics approach for the automatic design of a robot controller. The experiments were conducted by computer simulations with the path formation task. The results showed that the proposed approach succeeds in generating collective behavior in flat and rough terrain environments.

关键词： Swarm robotics evolutionary robotics Multi-legged robot

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Generating collective behavior of a multi-legged robotic swarm using an evolutionary robotics approach

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ARTIFICIAL LIFE AND robotics 2022年第4期27卷 751-760页

作者： Morimoto, Daichi Hiraga, Motoaki Shiozaki, Naoya Ohkura, Kazuhiro Munetomo, Masaharu Hiroshima Univ Hiroshima Japan Hokkaido Univ Informat Initiat Ctr Sapporo Hokkaido Japan

This paper demonstrates to generate a collective behavior of a multi-legged robotic swarm based on the evolutionary robotics approach. Most studies in swarm robotics are conducted using mobile robots driven by wheels. This paper focuses on generating collective behavior using a multi-legged robotic swarm. The evolutionary robotics approach is employed for designing a robot controller. The intuition-based constraint factors are incorporated into the fitness function to make the gait of robots similar to natural organisms. The experiment on a task of forming a line is conducted in computer simulations using the PyBullet physics engine. The robot controller is represented by a recurrent neural network with a single hidden layer. The experimental results show that proposed constraint factors successfully designed the robot's gait similar to natural organisms. The results also show that the evolutionary robotics approach successfully designed the robot controller for collective behavior of a multi-legged robotic swarm.

关键词： Swarm robotics evolutionary robotics Multi-legged robot

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General properties of the evolution of research fields: a scientometric study of human microbiome, evolutionary robotics and astrobiology

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SCIENTOMETRICS 2018年第2期117卷 1265-1283页

作者： Coccia, Mario CNR Natl Res Council Italy Rome Italy Arizona State Univ Tempe AZ 85287 USA IRCRES CNR Coll Carlo Alberto Via Real Coll 30 I-10024 Turin Italy

How do research fields evolve? This study confronts this question here by developing an inductive analysis based on emerging research fields of human microbiome, evolutionary robotics and astrobiology (also called exobiology). Data analysis considers papers associated with subject areas of authors from starting years to 2017 per each research field under study. Findings suggest some empirical properties of the evolution of research fields: the first property states that the evolution of a research field is driven by few disciplines (3-5) that generate more than 80% of documents (concentration of scientific production);the second property states that the evolution of research fields is path-dependent of critical disciplines: they can be parent disciplines that have originated the research field or new disciplines emerged during the evolution of science;the third property states that the evolution of research fields can be also due to a new discipline originated from a process of specialization within applied or basic sciences and/or convergence between disciplines. Finally, the fourth property states that the evolution of specific research fields can be due to both applied and basic sciences. These results here can explain and generalize some characteristics of the evolution ofscientific fields in the dynamics of science. Overall, then, this study begins the process of clarifying and generalizing, as far as possible, the generalproperties of the evolution of research fields to lay a foundation for the development of sophisticated theories of the evolution of science.

关键词： Research fields Evolution of science Dynamics of science Convergence in science Applied sciences Basic sciences Human microbiome evolutionary robotics Astrobiology Exobiology A19 C00 I23 L30

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Toward open-ended evolutionary robotics: evolving elementary robotic units able to self-assemble and self-reproduce

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CONNECTION SCIENCE 2004年第4期16卷 227-248页

作者： Bianco, R Nolfi, S CNR Inst Cognit Sci & Technol I-00137 Rome Italy

In this paper, we discuss the limitations of current evolutionary robotics models and we propose a new framework that might solve some of these problems and lead to an open-ended evolutionary process in hardware. More specifically, the paper describes a novel approach where the usual concepts of population, generations and fitness are made implicit in the system. Individuals co-evolve embedded in their environment. Exploiting the self-assembling capabilities of the (simulated) robots, the genotype of a successful individual can spread in the population. In this way, interesting behaviours emerge spontaneously, resulting in chasing and evading other individuals, collective obstacle avoidance and co-ordinated motion of self-assembled structures.

关键词： open-ended evolution self-assembling self-replication body-brain co-evolution evolutionary robotics

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Using direct competition to select for competent controllers in evolutionary robotics

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robotics AND AUTONOMOUS SYSTEMS 2006年第10期54卷 840-857页

作者： Nelson, Andrew L. Grant, Edward Androt LLC Tucson AZ 85733 USA N Carolina State Univ Ctr Robot & Intelligent Machines Raleigh NC 27695 USA

evolutionary robotics (ER) is a field of research that applies artificial evolution toward the automatic design and synthesis of intelligent robot controllers. The preceding decade saw numerous advances in evolutionary robotics hardware and software systems. However, the sophistication of resulting robot controllers has remained nearly static over this period of time. Here, we make the case that current methods of controller fitness evaluation are primary factors limiting the further development of ER. To address this, we define a form of fitness evaluation that relies on intra-population competition. In this research, complex neural networks were trained to control robots playing a competitive team game. To limit the amount of human bias or know-how injected into the evolving controllers, selection was based on whether controllers won or lost games. The robots relied on video sensing of their environment, and the neural networks required on the order of 150 inputs. This represents an order of magnitude increase in sensor complexity compared to other research in this field. Evolved controllers were tested extensively in real fully-autonomous robots and in simulation. Results and experiments are presented to characterize the training process and the acquisition of controller competency under different evolutionary conditions. (c) 2006 Elsevier B.V. All rights reserved.

关键词： evolutionary robotics learning robots evolutionary neural networks swarm robotics developmental robotics

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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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Towards robot vision using deep neural networks in evolutionary robotics

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evolutionary INTELLIGENCE 2022年第1期15卷 81-97页

作者： Watt, Nathan du Plessis, Mathys C. Nelson Mandela Univ Univ Way ZA-6019 Port Elizabeth South Africa

In evolutionary robotics, robot controllers are often evolved in simulation, as using the physical robot for fitness evaluation can take a prohibitively long time. Simulators provide a quick way to evaluate controller fitness. A simulator is tasked with providing appropriate sensor information to the controller. If the robot has an on-board camera, an entire virtual visual environment is needed to simulate the camera's signal. In the past, these visual environments have been constructed by hand, requiring the use of hand-crafted models, textures and lighting, which is a tedious and time-consuming process. This paper proposes a deep neural network-based architecture for simulating visual environments. The neural networks are trained exclusively from images captured from the robot, creating a 3-dimensional visual environment without using hand-crafted models, textures or lighting. It does not rely on any external domain specific datasets, as all training data is captured in the physical environment. Robot controllers were evolved in simulation to discern between objects with different colours and shapes, and they successfully completed the same task in the real world.

关键词： Computer vision evolutionary robotics Object detection Neural networks

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Evolvable hardware in evolutionary robotics

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AUTONOMOUS ROBOTS 2004年第1期16卷 5-21页

作者： Tan, KC Wang, LF Lee, TH Vadakkepat, P Natl Univ Singapore Dept Elect & Comp Engn Singapore 117576 Singapore

In recent decades the research on evolutionary robotics (ER) has developed rapidly. This direction is primarily concerned with the use of evolutionary computing techniques in the design of intelligent and adaptive controllers for robots. Meanwhile, much attention has been paid to a new set of integrated circuits named Evolvable Hardware (EHW), which is capable of reconfiguring its architectures unlimited time based on artificial evolution techniques. This paper surveys the application of evolvable hardware in evolutionary robotics. The evolvable hardware is an emerging research field concerning the development of evolvable robot controllers at the hardware level to adapt to dynamic changes in environments. The context of evolvable hardware and evolutionary robotics is reviewed, and a few representative experiments in the field of robotic hardware evolution are presented. As an alternative to conventional robotic controller designs, the potentialities and limitations of the EHW-based robotic system are discussed and summarized.

关键词： evolutionary robotics evolvable hardware autonomous robots

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