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Behavior Trees for evolutionary robotics

ARTIFICIAL LIFE 2016年第1期22卷 23-48页

作者： Scheper, Kirk Y. W. Tijmons, Sjoerd de Visser, Cornelis C. de Croon, Guido C. H. E. Delft Univ Technol Fac Aerosp Engn NL-2629 HS Delft Netherlands

evolutionary robotics allows robots with limited sensors and processing to tackle complex tasks by means of sensory-motor coordination. In this article we show the first application of the Behavior Tree framework on a real robotic platform using the evolutionary robotics methodology. This framework is used to improve the intelligibility of the emergent robotic behavior over that of the traditional neural network formulation. As a result, the behavior is easier to comprehend and manually adapt when crossing the reality gap from simulation to reality. This functionality is shown by performing real-world flight tests with the 20-g DelFly Explorer flapping wing micro air vehicle equipped with a 4-g onboard stereo vision system. The experiments show that the DelFly can fully autonomously search for and fly through a window with only its onboard sensors and processing. The success rate of the optimized behavior in simulation is 88%, and the corresponding real-world performance is 54% after user adaptation. Although this leaves room for improvement, it is higher than the 46% success rate from a tuned user-defined controller.

关键词： Behavior tree evolutionary robotics reality gap micro air vehicle

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Open Issues in evolutionary robotics

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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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evolutionary Developmental robotics: Improving Morphology and Control of Physical Robots

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ARTIFICIAL LIFE 2017年第2期23卷 169-185页

作者： Vujovic, Vuk Rosendo, Andre Brodbeck, Luzius Iida, Fumiya ETH Inst Robot & Intelligent Syst Zurich Switzerland Univ Cambridge Dept Engn Trumpington St Cambridge CB2 1PZ England

evolutionary algorithms have previously been applied to the design of morphology and control of robots. The design space for such tasks can be very complex, which can prevent evolution from efficiently discovering fit solutions. In this article we introduce an evolutionary-developmental (evo-devo) experiment with real-world robots. It allows robots to grow their leg size to simulate ontogenetic morphological changes, and this is the first time that such an experiment has been performed in the physical world. To test diverse robot morphologies, robot legs of variable shapes were generated during the evolutionary process and autonomously built using additive fabrication. We present two cases with evo-devo experiments and one with evolution, and we hypothesize that the addition of a developmental stage can be used within robotics to improve performance. Moreover, our results show that a nonlinear system-environment interaction exists, which explains the nontrivial locomotion patterns observed. In the future, robots will be present in our daily lives, and this work introduces for the first time physical robots that evolve and grow while interacting with the environment.

关键词： evolutionary robotics developmental robotics evo-devo genetic algorithms ontogeny phylogenetic

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Using Standard Components in evolutionary robotics to Produce an Inexpensive Robot Arm 7th

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7th World Congress on Nature and Biologically Inspired Computing (NaBIC)

作者： Louwrens, Michael W. du Plessis, Mathys C. Greyling, Jean H. Nelson Mandela Meteropolitan Univ Univ Way ZA-6031 Port Elizabeth South Africa

ISBN: (纸本)9783319274003;9783319273990

evolutionary robotics (ER) makes use of evolutionary algorithms to evolve controllers and morphologies of robots. Despite successful demonstrations in laboratory experiments, ER has not been widely adopted by industry as means of robot design. A possible reason for this is that current ER approaches ignore issues that are important when designing robots for practical use. For example, the availability and cost of components used for robot construction should be considered. A robot designed by the ER process may require specialised custom components to be built to support the physical functioning of the design, if the components selected by an ER process are not widely available. Alternatively, the ER designed robot may be too expensive to be constructed. This paper demonstrates that standard off-the-shelf components can be used by the ER process to design a robot. A robot arm is used as a sample problem, which is successfully optimised to use components from a fixed list while minimising cost.

关键词： evolutionary robotics evolutionary computing Standard components

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An evolutionary robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap 10

An Evolutionary Robotics Approach to the Control of Plant Gr...

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10th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO)

作者： Wahby, Mostafa Hofstadler, Daniel Nicolas Heinrich, Mary Katherine Zahadat, Payam Hamann, Heiko Univ Paderborn Heinz Nixdorf Inst Dept Comp Sci Paderborn Germany Karl Franzens Univ Graz Dept Zool Artificial Life Lab Graz Austria Royal Danish Acad Ctr IT & Architecture Sch Architecture Copenhagen Denmark Tech Univ Chemnitz Dept Comp Sci Chemnitz Germany

ISBN: (纸本)9781509035342

The self-organizing bio-hybrid collaboration of robots and natural plants allows for a variety of interesting applications. As an example we investigate how robots can be used to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionary robotics approach where task performance is determined by monitoring the plant's reaction. First, we do initial plant experiments with simple, predetermined controllers. Then we use image sampling data as a model of the dynamics of the plant tip xy position. Second, we use this approach to evolve robot controllers in simulation. The task is to make the plant approach three predetermined, distinct points in an xy-plane. Finally, we test the evolved controllers in real plant experiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tip to many points on the plant, for a model of the plant stem dynamics. Future work will extend to two-axes image sampling for a 3-d approach.

关键词： bio-hybrid evolutionary robotics plant modeling reality gap self-organization

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evolutionary robotics in two decades: A review

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2015年第4期40卷 1169-1184页

作者： Gupta, Sameer Singla, Ekta IIT Ropar Sch Mech Mat & Energy Engn Rupnagar 140001 India

evolutionary robotics (ER) has emerged as a fast growing field in the last two decades and has earned the attention of a number of researchers. Principles of biological evolution are applied in the form of evolutionary techniques for solving the complicated problems in the areas of robotic design and control. The diversity and the intensity of this growing field is presented in this paper through the contributions made by several researchers in the categories of robot controller design, robot body design, co-evolution of body and brain and in transforming the evolved robots in physical reality. The paper discusses some of the recent achievements in each of these fields along with some expected applications which are likely to motivate the future research. For the quick reference of the readers, a digest of all the works is presented in the paper, spanning the years and the areas of the research contributions.

关键词： evolutionary robotics evolutionary control robot morphology body brain design

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evolutionary robotics techniques used to model information and control of visually guided braking

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ADAPTIVE BEHAVIOR 2015年第3期23卷 125-142页

作者： Kadihasanoglu, Didem Beer, Randall D. Bingham, Geoffrey P. TOBB Univ Econ & Technol Dept Psychol TR-06560 Ankara Turkey Indiana Univ Cognit Sci Program Bloomington IN USA Indiana Univ Sch Informat & Comp Bloomington IN USA Indiana Univ Dept Psychol & Brain Sci Bloomington IN USA

This paper utilizes evolutionary robotics techniques as a hypothesis generator to explore optical variables and control strategies that could be used to solve a driving-like braking task. Given such a task, humans exhibit two different braking behaviors: continuously regulated braking and impulsive braking. Based on an oft-used experimental task in human perception/action research, a series of evolutionary robotics simulations were developed to explore the space of possible braking strategies by examining how braking strategies change as the optical information is manipulated. Our results can be summarized as follows: (1) behaviors similar to human behavior were observed only when the constraints were selected correctly;(2) the optical variables and proportional rate yielded significantly better braking performance;(3) two different classes of impulsive braking behaviors were observed, including one not reported in previous studies: discrete impulsive braking and oscillatory impulsive braking;(4) the optical variable is used to initiate and terminate braking;(5) the evolved model agents use a proportional rate control strategy to regulate braking continuously. We argue that combining psychological experiments and evolutionary robotics simulations is a promising research methodology that is useful for testing existing hypotheses and generating new ones.

关键词： evolutionary robotics visually guided braking proportional rate control constant tau-dot strategy

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evolutionary robotics on Lego NXT Platform 27

Evolutionary Robotics on Lego NXT Platform

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27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Poikselka, Katja Vallivaara, Ilari Roning, Juha Univ Oulu Dept Comp Sci & Engn SF-90100 Oulu Finland

ISBN: (纸本)9781509001637

This paper studies the Lego NXT platform's suitability for evolutionary robotics. It is shown that the low-cost Lego NXT educational set is indeed adequate for simple experiments in evolutionary robotics. This is demonstrated by an experiment, where an artificial neural network-based controller capable of behaving meaningfully in a Lego sumo wrestling context is evolved on physical Lego NXT robots without the aid of simulation. A detailed description of the experiment is provided, and the practical aspects of actually conducting evolutionary robotics on the platform are studied. Earlier research suggests that using evolutionary robotics in education could provide a good and concrete example of the principles and mechanisms of evolution. The research described here utilizes only standard Lego NXT Educational kits, making conducting the experiments possible for a very wide audience. To the authors' knowledge this is the first time the non-simulated Lego NXT is used to conduct artificial neural network-based evolutionary robotics.

关键词： evolutionary robotics Neural networks Lego NXT

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Investigating intertemporal choice through experimental evolutionary robotics

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BEHAVIOURAL PROCESSES 2015年 115卷 1-18页

作者： Paglieri, Fabio Parisi, Domenico Patacchiola, Massimiliano Petrosino, Giancarlo ISTC CNR Goal Oriented Agents Lab Rome Italy ISTC CNR Lab Artificial Life & Robot LARAL Rome Italy Univ Plymouth Sch Comp & Math Ctr Robot & Neural Syst Plymouth PL4 8AA Devon England

In intertemporal choices, subjects face a trade-off between value and delay: achieving the most valuable outcome requires a longer time, whereas the immediately available option is objectively poorer. Intertemporal choices are ubiquitous, and comparative studies reveal commonalities and differences across species: all species devalue future rewards as a function of delay (delay aversion), yet there is a lot of inter-specific variance in how rapidly such devaluation occurs. These differences are often interpreted in terms of ecological rationality, as depending on environmental factors (e.g., feeding ecology) and the physiological and morphological constraints of different species (e.g., metabolic rate). evolutionary hypotheses, however, are hard to verify in vivo, since it is difficult to observe precisely enough real environments, not to mention ancestral ones. In this paper, we discuss the viability of an approach based on evolutionary robotics: in Study 1, we evolve robots without a metabolism in five different ecologies;in Study 2, we evolve metabolic robots (i.e., robots that consume energy over time) in three different ecologies. The intertemporal choices of the robots are analyzed both in their ecology and under laboratory conditions. Results confirm the generality of delay aversion and the usefulness of studying intertemporal choice through experimental evolutionary robotics. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Intertemporal choice evolutionary robotics Ecological rationality Delay discounting Spatial discounting Preferences

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