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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References
Tedeschi, F., Carbone, G.: Design issues for hexapod walking robots. Robotics 3, 181–206 (2014)
International Federation of Robotics. http://www.ifr.org/
Chavez-Clemente, D.: Gait optimization for multi-legged walking robots, with application to a lunar hexapod (2011). http://purl.stanford.edu/px063cb7934Includes
Carbone, G., Ceccarelli, M.: A mechanical design of a low-cost easy-operation anthropomorphic wheeled leg for walking machines. Int. J. Robot. Manag. 9, 3–8 (2004)
De Santos, P.G., Garcia, E., Estremera, J.: Quadrupedal locomotion: an introduction to the control of four-legged robots. Springer, London (2006)
Krotkov, E.P., Simmons, R.G., Whittaker, W.L.: Ambler: performance of a six-legged planetary rover. Acta Astronaut. 35, 75–81 (1995)
Nonami, K., Barai, R.K., Irawan, A., Daud, M.R.: Hydraulically Actuated Hexapod Robots: Design, Implementation and Control. Intelligent Systems, Control and Automation: Science and Engineering, vol. 66. Springer, Heidelberg (2014)
Silva, M.F., Machado, J.A.T., Barbosa, R.S.: Complex-order dynamics in hexapod locomotion. Sig. Process. 86, 2785–2793 (2006)
Coello, C.A.C., Lamont, G.B., Van Veldhuizen, D.A: Evolutionary Algorithms for Solving Multi-objective Problems, 2nd edn. Springer, Heidelberg (2007)
Deb, K.: Multi-objective Optimization Using Evolutionary Algorithms. Wiley, New York (2001)
Marler, R.T., Arora, J.S.: Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. Optim. 26, 369–395 (2004)
Ascia, G., Catania, V., Di Nuovo, A.G., Palesi, M., Patti, D.: Performance evaluation of efficient multi-objective evolutionary algorithms for design space exploration of embedded computer systems. Appl. Soft Comput. 11, 382–398 (2011)
Mukhopadhyay, A., Maulik, U., Bandyopadhyay, S., Coello, C.A.C.: A survey of multiobjective evolutionary algorithms for data mining: part i. IEEE Trans. Evol. Comput. 18, 4–19 (2014)
Mukhopadhyay, A., Maulik, U., Bandyopadhyay, S., Coello, C.A.C.: Survey of multiobjective evolutionary algorithms for data mining: part II. IEEE Trans. Evol. Comput. 18(1), 20–35 (2014)
Di Nuovo, A., Palesi, M., Catania, V.: Multi-objective evolutionary fuzzy clustering for high-dimensional problems. In: IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2007, pp. 1–6. IEEE (2007)
Di Nuovo, A., Catania, V.: An evolutionary fuzzy c-means approach for clustering of bio-informatics databases. In: IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence), pp. 2077–2082. IEEE (2008)
Ponsich, A., Jaimes, A.L., Coello, C.A.C.: A survey on multiobjective evolutionary algorithms for the solution of the portfolio optimization problem and other finance and economics applications. IEEE Trans. Evol. Comput. 17, 321–344 (2013)
Deb, K., Tiwari, S.: Multi-objective optimization of a leg mechanism using genetic algorithms. Eng. Optim. 37, 325–350 (2005)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6, 182–197 (2002)
Fleming, P.J., Pashkevich, A.P.: Application of multi-objective optimisation to compensator design for SISO control systems. Electron. Lett. 22(1), 258–259 (1986)
Schittkowski, K.: NLPQL: A fortran subroutine solving constrained nonlinear programming problems. Ann. Oper. Res. 5, 485–500 (1986)
Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., Da Fonseca, V.G.: Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans. Evol. Comput. 7(2), 117–132 (2003)
Tedeschi, F., Carbone, G.: Design of hexapod walking robots: background and challenges. In: Habib, M.K. (ed.) Handbook of Research on Advancements in Robotics and Mechatronics, pp. 527–566. IGI Global (2015)
Di Nuovo, A.G., Ascia, G., Catania, V.: A study on evolutionary multi-objective optimization with fuzzy approximation for computational expensive problems. In: Coello, C.A., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds.) PPSN 2012, Part II. LNCS, vol. 7492, pp. 102–111. Springer, Heidelberg (2012)
Carbone, G., Shrot, A., Ceccarelli, M.: Operation strategy for a low-cost easy operation Cassino Hexapod. Appl. Bionics Biomech. 4, 149–156 (2007)
Carbone, G., Tedeschi, F.: A low cost control architecture for Cassino Hexapod II. Int. J. Mech. Control. 14, 19–24 (2013)
Carbone, G., Ceccarelli, M., Oliveira, P., Saramago, S.: Carvalho, J, F.: An optimum path planning for Cassino parallel manipulator by using inverse dynamics. Robotica 6, 229–239 (2008)
Carbone, G., Tedeschi, F., Gallozzi, A., Cigol, M.: A robotic mobile platform for service tasks in cultural heritage. Int. J. Adv. Robot. Syst. 12, 1–10 (2015)
Frankovský, P., Hroncová, D., Delyová, I., Hudák, P.: Inverse and forward dynamic analysis of two link manipulator. In: Procedia Engineering, pp. 158–163 (2012)
Mann, H.B., Whitney, D.R.: On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947)
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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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