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A Hybrid Multi-objective Evolutionary Approach for Optimal Path Planning of a Hexapod Robot

A Preliminary Study

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Hybrid Metaheuristics (HM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9668))

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Abstract

Hexapod robots are six-legged robotic systems, which have been widely investigated in the literature for various applications including exploration, rescue, and surveillance. Designing hexapod robots requires to carefully considering a number of different aspects. One of the aspects that require careful design attention is the planning of leg trajectories. In particular, given the high demand for fast motion and high-energy autonomy it is important to identify proper leg operation paths that can minimize energy consumption while maximizing the velocity of the movements. In this frame, this paper presents a preliminary study on the application of a hybrid multi-objective optimization approach for the computer-aided optimal design of a legged robot. To assess the methodology, a kinematic and dynamic model of a leg of a hexapod robot is proposed as referring to the main design parameters of a leg. Optimal criteria have been identified for minimizing the energy consumption and efficiency as well as maximizing the walking speed and the size of obstacles that a leg can overtake. We evaluate the performance of the hybrid multi-objective evolutionary approach to explore the design space and provide a designer with an optimal setting of the parameters. Our simulations demonstrate the effectiveness of the hybrid approach by obtaining improved Pareto sets of trade-off solutions as compared with a standard evolutionary algorithm. Computational costs show an acceptable increase for an off-line path planner.

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Author information

Authors and Affiliations

  1. Department of Engineering and Mathematics, Sheffield Hallam University, Sheffield, UK

    Giuseppe Carbone

  2. Department of Computing, Sheffield Hallam University, Sheffield, UK

    Alessandro Di Nuovo

  3. Department of Civil and Mechanical Engineering, University of Cassino and South Latium, Cassino, Italy

    Giuseppe Carbone

  4. Faculty of Engineering and Architecture, University of Enna “Kore”, Enna, Italy

    Alessandro Di Nuovo

Authors
  1. Giuseppe Carbone
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  2. Alessandro Di Nuovo
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Corresponding author

Correspondence to Giuseppe Carbone .

Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    Maria J. Blesa

  2. University of the Basque Country, San Sebastian, Spain

    Christian Blum

  3. Universiy of Plymouth, Plymouth, United Kingdom

    Angelo Cangelosi

  4. University of Catania, Catania, Italy

    Vincenzo Cutello

  5. Computing, Sheffield Hallam University, SHEFFIELD, United Kingdom

    ALESSANDRO DI NUOVO

  6. University of Catania, Catania, Italy

    Mario Pavone

  7. University of Lille 1, Villeneuve d'Ascq, France

    El-Ghazali Talbi

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Carbone, G., Di Nuovo, A. (2016). A Hybrid Multi-objective Evolutionary Approach for Optimal Path Planning of a Hexapod Robot. In: Blesa, M., et al. Hybrid Metaheuristics. HM 2016. Lecture Notes in Computer Science(), vol 9668. Springer, Cham. https://doi.org/10.1007/978-3-319-39636-1_10

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  • DOI: https://doi.org/10.1007/978-3-319-39636-1_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39635-4

  • Online ISBN: 978-3-319-39636-1

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