Automatic generation of a controller for an autonomous agent based on gate growth

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This article was downloaded by: [TIB & Universitaetsbibliothek]On: 28 October 2014, At: 03:54Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UKAdvanced RoboticsPublication details, including instructions for authorsand subscription information: generation of acontroller for an autonomousagent based on gate growthKensuke Takita a & Yukinori Kakazu ba Tokyo Institute of Technology, 2-12-1 Ookayama,Meguro-ku, Tokyo 152-8552, Japanb Hokkaido University, N13W8 Kita-Ku, Sapporo,Hokkaido 060-0813, JapanPublished online: 02 Apr 2012.To cite this article: Kensuke Takita & Yukinori Kakazu (1998) Automatic generation ofa controller for an autonomous agent based on gate growth, Advanced Robotics, 13:3,247-248, DOI: 10.1163/156855399X00432To link to this article: SCROLL DOWN FOR ARTICLETaylor & Francis makes every effort to ensure the accuracy of all the information(the Content) contained in the publications on our platform. However, Taylor& Francis, our agents, and our licensors make no representations or warrantieswhatsoever as to the accuracy, completeness, or suitability for any purposeof the Content. Any opinions and views expressed in this publication are theopinions and views of the authors, and are not the views of or endorsed byTaylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor andFrancis shall not be liable for any losses, actions, claims, proceedings, demands,costs, expenses, damages, and other liabilities whatsoever or howsoever causedarising directly or indirectly in connection with, in relation to or arising out of theuse of the Content.This article may be used for research, teaching, and private study purposes.Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly Terms & Conditions of access and use can be found at by [TIB & Universitaetsbibliothek] at 03:55 28 October 2014 generation of a controller for an autonomous agent based on gate growth KENSUKE TAKITA 1 and YUKINORI KAKAZU 2 1 Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8552, Japan 2 Hokkaido University, N13W8 Kita-Ku, Sapporo, Hokkaido 060-0813, Japan E-mail: Keywords: Evolutionary robotics; gate; subsumption architecture; gate growth. INTRODUCTION In this paper, we propose 'gate growth', which is a methodology to develop an autonomous agent, and show experiments with the method. The objective of experiments is to examine the ability to create adequate reactive rules with the proposal method and to develop real autonomous robots. Gate growth consists of two concepts: the connection mechanism and NAND array. The NAND array is a device model consisting of an array of NAND elements. The connection mechanism makes connections among these elements. We employed cellular automaton (CA) as a connection mechanism and genetic algorithms (GAs) as renewing algorithms for the rules. To examine the proposed method, we applied it to the 'wall-following problem' with the miniature robot Khepera. EXPERIMENT Experimental setting We applied the proposed method to the 'wall-following problem' to examine its perfor- mance. In order to resolve the problem, we implemented the NAND array as the mimic- information generator in the architecture that we call 'mimic reactive architecture'. Control structure We adopt subsumption architecture as the fundamental control style. The fundamental tendency of behaviors is avoid objects (Fig. 1). In order to make the agent follow walls, the NAND array makes the appropriate mimic-information to cheat the sensor inputs. In the following section, we describe the array structure and GA operations. Downloaded by [TIB & Universitaetsbibliothek] at 03:55 28 October 2014 248 Figure 1. Control structure in the agent. Figure 2. Input value for the NAND array. Figure 3. Wall-following behavior. NAND array In this experiment, we use a NAND array as an 8-input/8-output function in order to examine the possibility that the rules in CA evolve properly through GA operation, which has 20 individuals. Each sensor reading is interpreted as a 0/1 string as input to the NAND array. After calculating with the implemented function, the NAND array output of the 8-bit string shown in Fig. 2 is O. The rule sets in the NAND array are evaluated according to the sensor reading and wheel speed. GA operation changes the rules according to this fitness value. Through generation, the NAND array acquires the proper function. Result Equation (1) and Fig. 3 show one of the successful functions and its behavior. If the sensors detect nothing, the NAND array generates the walls on the right side, hence the agent goes between real and virtual walls. CONCLUSION This paper looked at an evolutionary approach to robotics. Through experiment, we confirm that it is possible to realize the appropriate control rule on the NAND circuit. However, various structures can achieve a task. In order to generate a valid circuit, we have to deliberate and search for a suitable fitness function for a given task. This still causes difficulty in the design of autonomous agents. Downloaded by [TIB & Universitaetsbibliothek] at 03:55 28 October 2014


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