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Genetic programming-based self-reconfiguration planning for metamorphic robot

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Abstract

This paper presents a genetic programming based reconfiguration planner for metamorphic modular robots. Initially used for evolving computer programs that can solve simple problems, genetic programming (GP) has been recently used to handle various kinds of problems in the area of complex systems. This paper details how genetic programming can be used as an automatic programming tool for handling reconfiguration-planning problem. To do so, the GP evolves sequences of basic operations which are required for transforming the robot’s geometric structure from its initial configuration into the target one while the total number of modules and their connectedness are preserved. The proposed planner is intended for both Crystalline and TeleCube modules which are achieved by cubical compressible units. The target pattern of the modular robot is expressed in quantitative terms of morphogens diffused on the environment. Our work presents a solution for self reconfiguration problem with restricted and unrestricted free space available to the robot during reconfiguration. The planner outputs a near optimal explicit sequence of low-level actions that allows modules to move relative to each other in order to form the desired shape.

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Authors and Affiliations

  1. LESIA Laboratory, University of Biskra, PO Box 145 RP, Biskra, 07000, Algeria

    Tarek Ababsa & Noureddine Djedl

  2. IRIT Laboratory, University of Toulouse 1 Capitole, 21 Alles de Brinne, Toulouse, 31032, France

    Yves Duthen

Authors
  1. Tarek Ababsa
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  2. Noureddine Djedl
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  3. Yves Duthen
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Correspondence to Tarek Ababsa.

Additional information

Recommended by Associate Editor Min Tan

Tarek Ababsa received the B. Sc. and M. Sc. degrees in computer science from the University of Biskra, Algeria in 2004 and 2008, respectively. Since 2009, he is a professor in the Department of Computer Sciences at University of Biskra, Algeria. He has published two refereed conference papers. He received the fourth Best Poster Award of the Alife International Conference in 2014 (New York).

His research interests include robotics, complex systems, and evolutionary algorithms.

Noureddine Djedi received the B. Sc. degree in computer science from USTHB University, Algeria in 1986. He received the M. Sc. and Ph.D. degrees in computer graphics from Paul Sabatier respextively University (Toulouse III), France in 1987 and 1991, respectively. He was the head of LESIA Laboratory from 2008 to 2011. He has published about 70 refereed journal and conference papers.

His research interests include robotics, image synthesis, artificial life and behavioural animation.

Yves Duthen received the Ph.D. degree from the University Paul Sabatier, France in 1983, and the French Habilitation degree in 1993 to become full professor. He is a research professor of artificial life and virtual reality at IRIT Lab, University of Toulouse 1-Capitole, France. He has worked in Image Synthesis during the 1980s and focused on behavioural simulation based on evolutionary mechanism since 1990. He has published about 130 refereed journal and conference papers and has directed 15 Ph.D. thesis.

He has pioneered research in artificial life for building adaptive artificial creatures and focuses now on embedded metabolism and morphogenetic engineering.

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Ababsa, T., Djedl, N. & Duthen, Y. Genetic programming-based self-reconfiguration planning for metamorphic robot. Int. J. Autom. Comput. 15, 431–442 (2018). https://doi.org/10.1007/s11633-016-1049-4

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  • DOI: https://doi.org/10.1007/s11633-016-1049-4

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