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Employing Cellular Automata for Shaping Accurate Morphology Maps Using Scattered Data from Robotics’ Missions

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Book cover Robots and Lattice Automata

Part of the book series: Emergence, Complexity and Computation ((ECC,volume 13))

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Abstract

Accurate maps are essential in the case of robot teams, so that they can operate autonomously and accomplish their tasks efficiently. In this work we present an approach which allows the generation of detailed maps, suitable for robot navigation, from a mesh of sparse points using Cellular Automata and simple evolutions rules. The entire map area can be considered as a 2D Cellular Automaton (CA) where the value at each CA cell represents the height of the ground in the corresponding coordinates. The set of measurements form the original state of the CA. The CA rules are responsible for generating the intermediate heights among the real measurements. The proposed method can automatically adjust its rules, so as to encapture local morphological attributes, using a pre-processing procedure in the set of measurements. The main advantage of the proposed approach is the ability to maintain an accurately reconstruction even in cases where the number of measurements are significant reduced. Experiments have been conducted employing data collected from two totally different real-word environments. In the first case the proposed approach is applied, so as to build a detailed map of a large unknown underwater area in Oporto, Portugal. The second case concerns data collected by a team of aerial robots in real experiments in an area near Zurich, Switzerland and is also used for the evaluation of the approach. The data collected, in the two aforementioned cases, are extracted using different kind of sensors and robots, thus demonstrating the applicability of our approach in different kind of devices. The proposed method outperforms the performance of other well-known methods in literature thus enabling its application for real robot navigation.

The research leading to these results has received funding from the European Communities Seventh Framework Programme (FP7/2007–2013) under grant agreements n. 270180 (NOPTILUS)

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Notes

  1. 1.

    We will assume that the robot’s measurements are filtered and free of bias/Gaussian noise. It has to be emphasized that the proposed approach can be extended to deal with noisy data giving weights about the confidence level of the measurement’s accuracy.

  2. 2.

    Note that now and in the next experiments there has not been any analysis about the distribution that is followed by the measurements. Different modalities, like different number of robots or different type of sensors, etc., will lead to a different data distribution. The above problem is tackled by conducted the same experiment 500 times with the initial measurements stochastically changed and keep the average of error.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100, Xanthi, GR, Greece

    Athanasios Ch. Kapoutsis, Savvas A. Chatzichristofis, Georgios Ch. Sirakoulis & Elias B. Kosmatopoulos

  2. Telematics Institute, Center for Research and Technology, Hellas (ITI-CERTH), 57001, Thessaloniki, Greece

    Athanasios Ch. Kapoutsis, Savvas A. Chatzichristofis, Georgios Ch. Sirakoulis, Lefteris Doitsidis & Elias B. Kosmatopoulos

  3. Department of Electronic Engineering, Technological Educational Institute of Crete, 73100, Chania, GR, Greece

    Lefteris Doitsidis

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  1. Athanasios Ch. Kapoutsis
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  2. Savvas A. Chatzichristofis
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  3. Georgios Ch. Sirakoulis
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  4. Lefteris Doitsidis
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  5. Elias B. Kosmatopoulos
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Correspondence to Athanasios Ch. Kapoutsis .

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Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece

    Georgios Ch. Sirakoulis

  2. Unconventional Computing Centre, University of the West of England, Bristol, United Kingdom

    Andrew Adamatzky

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Kapoutsis, A.C., Chatzichristofis, S.A., Sirakoulis, G.C., Doitsidis, L., Kosmatopoulos, E.B. (2015). Employing Cellular Automata for Shaping Accurate Morphology Maps Using Scattered Data from Robotics’ Missions. In: Sirakoulis, G., Adamatzky, A. (eds) Robots and Lattice Automata. Emergence, Complexity and Computation, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-10924-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-10924-4_10

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