Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T19:40:02.853Z Has data issue: false hasContentIssue false

Design of a customized humanoid robot with coevolution of body morphology and its locomotion

Published online by Cambridge University Press:  14 February 2022

Jiwen Zhang
Affiliation:
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
Xunlei Shi*
Affiliation:
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
Chenglong Fu
Affiliation:
Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Li Liu
Affiliation:
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
Ken Chen
Affiliation:
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
*
*Corresponding author. E-mail: [email protected]

Abstract

An important goal for humanoid robots is to achieve fast, flexible and stable walking. In previous research, the structure and walking algorithms evolved separately, resulting in a slow evolution speed and lack of an initial design basis. This paper proposes comprehensively considering body morphology and walking patterns, exploring the relationship between them and their influence on the motion ability. The method parameterizes the body morphology and walking patterns. Then a response surface model is established to describe the complex relationship between these parameters and finally obtain the optimized parameters, which provides a reference for the structural design and gait generation.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Huang, Q., Yokoi, K., Kajita, S., Kaneko, K., Arai, H., Koyachi, N. and Tanie, K., “Planning walking patterns for a biped robot,” IEEE Trans. Rob. Autom. 17(3), 280289 (2001).CrossRefGoogle Scholar
Kajita, S., Hirukawa, H., Harada, K. and Yokoi, K., “Biped Walking,” In: Introduction to Humanoid Robotics, Springer Tracts in Advanced Robotics, vol. 101 (Springer, Berlin, Heidelberg).Google Scholar
Fu, C., Tan, F. and Chen, K., “A simple walking strategy for biped walking based on an intermittent sinusoidal oscillator,” Robotica 28(6), 869884 (2010).CrossRefGoogle Scholar
Da, X., Harib, O., Hartley, R., Griffin, B. and Grizzle, J. W., “From 2D design of underactuated bipedal gaits to 3d implementation: Walking with speed tracking,” IEEE Access 4(1), 34693478 (2017).CrossRefGoogle Scholar
Goldbeck, C., Kaul, L., Vahrenkamp, N., Worgotter, F., Asfour, T. and Braun, J. M., “Two Ways of Walking: Contrasting a Reflexive Neuro-Controller and a LIP-based ZMP-Controller on the Humanoid Robot ARMAR-4,” IEEE-RAS, International Conference on Humanoid Robots (IEEE, 2017) pp. 966972.CrossRefGoogle Scholar
Gouaillier, D., Hugel, V., Blazevic, P., Kilner, C. and Maisonnier, B., “Mechatronic Design of NAO Humanoid,” 2009 IEEE International Conference on Robotics and Automation (IEEE, 2009) pp. 769774.CrossRefGoogle Scholar
Hirose, M. and Ogawa, K., “Honda humanoid robots development,” Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 365(1850), 1119 (2006).CrossRefGoogle Scholar
Kuindersma, S., Deits, R., Fallon, M., Valenzuela, A., Dai, H., Permenter, F., Koolen, T., Marion, P. and Tedrake, R., “Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot,” Autonomous Robots 40(3), 429455 (2016).CrossRefGoogle Scholar
Moro, F. L., Tsagarakis, N. G. and Caldwell, D. G., “Walking in the resonance with the COMAN robot with trajectories based on human kinematic motion primitives (kMPs),” Auton. Robots 36(4), 331347 (2014).CrossRefGoogle Scholar
Torricelli, D., Gonzalez, J., Weckx, M., Jiménez-Fabián, R., Vanderborght, B., Sartori, M., Dosen, S., Farina, D., Lefeber, D. and Pons, J. L., “Human-like compliant locomotion: State of the art of robotic implementations,” Bioinspiration Biomimetics 11(5), 051002 (2016).CrossRefGoogle ScholarPubMed
Buschmann, T., Lohmeier, S. and Ulbrich, H., “Humanoid robot lola: Design and walking control,” J. Physiol. Paris 103(3–5), 141148 (2009).CrossRefGoogle ScholarPubMed
Park, I. W., Kim, J. Y., Lee, J. and Oh, J. H., “Mechanical design of the humanoid robot platform, HUBO,” Advanced Robotics 21(11), 13051322 (2007).CrossRefGoogle Scholar
Lohmeier, S., Buschmann, T., Schwienbacher, M., Ulbrich, H. and Pfeiffer, F., “Leg Design for a Humanoid Walking Robot,” 2006 6th IEEE-RAS International Conference on Humanoid Robots (IEEE, 2006) pp. 536541.CrossRefGoogle Scholar
Gong, D., Yan, J. and Zuo, G., “A review of gait optimization based on evolutionary computation,” Appl. Comput. Intell. Soft Comput 2010(413179), 112 (2010).Google Scholar
Xia, Z., Liu, L., Jing, X., Qiang, Y. and Chen, K., “Design aspects and development of humanoid robot THBIP-2,” ROBOTICA 26(1), 109116 (2008).CrossRefGoogle Scholar
Endo, K., Maeno, T. and Kitano, H., “Co-Evolution of Morphology and Walking Pattern of Biped Humanoid Robot Using Evolutionary Computation: Designing the Real Robot,” IEEE International Conference on Robotics and Automation, 2003. Proceedings. ICRA, vol. 1 (IEEE, 2003) pp. 13621367.Google Scholar
Endo, K., Yamasaki, F., Maeno, T. and Kitano, H., “A Method for Co-Evolving Morphology and Walking Pattern of Biped Humanoid Robot,” IEEE International Conference on Robotics and Automation, 2002. Proceedings. ICRA, vol. 3 (IEEE, 2002) pp. 27752780.Google Scholar
Eaton, M., “Further explorations in evolutionary humanoid robotics,” Artif. Life Rob. 12(1–2), 133137 (2008).CrossRefGoogle Scholar
Jouandeau, N. and Hugel, V., “Simultaneous Evolution of Leg Morphology and Walking Skills to Build the Best Humanoid Walker,” IEEE-RAS International Conference on Humanoid Robots (2013).Google Scholar
Collins, S. H. and Ruina, A., “A Bipedal Walking Robot with Efficient and Human-like Gait,” Proceedings of 2005 IEEE International Conference on Robotics and Automation (IEEE, 2005) pp. 19831988.Google Scholar
Nolfi, S., Bongard, J., Husbands, P. and Floreano, D., “Evolutionary Robotics,” In: Springer Handbook of Robotics (Springer, Cham, 2016) pp. 20352068.CrossRefGoogle Scholar
Sacks, J., Welch, W. J., Mitchell, T. J. and Wynn, H. P., “Design and analysis of computer experiments,” Stat. Sci. 4(4), 409435 (1989).Google Scholar
Jones, D. R., Schonlau, M. and Welch, W. J., “Efficient global optimization of expensive black-box functions,” J. Global Optim. 13(4), 455492 (1998).CrossRefGoogle Scholar
Lee, J. and Oh, J. H., “Biped walking pattern generation using reinforcement learning,” Int. J. Humanoid Rob. 6(01), 121 (2009).CrossRefGoogle Scholar
Silva, I. J., Perico, D. H., Homem, T. P. D., Vilo, C. O. and Bianchi, R. A. C., “Using Reinforcement Learning to Improve the Stability of a Humanoid Robot: Walking on Sloped Terrain,” 2015 12th Latin American Robotics Symposium and 2015 3rd Brazilian Symposium on Robotics (LARS-SBR) (IEEE, 2015) pp. 210215.CrossRefGoogle Scholar
Silva, I. J., Perico, D. H., Costa, A. H. R. and Bianchi, R. A. D. C., “Using reinforcement learning to optimize gait generation parameters of a humanoid robot,” XIII Simpósio Brasileiro de Automaçao Inteligente (2017).Google Scholar
Hemker, T., Stelzer, M. and Stryk, O. V., “Efficient walking speed optimization of a humanoid robot,” Int. J. Rob. Res. 28(2), 303314 (2009).CrossRefGoogle Scholar
Zhang, J., Xia, Z., Liu, L. and Chen, K., “Footstep adaptation strategy for reactive omnidirectional walking in humanoid robots,” Robotica 36(1), 5777 (2018).CrossRefGoogle Scholar
Roustant, O., Ginsbourger, D. and Deville, Y., “DiceKriging, DiceOptim: Two R packages for the analysis of computer experiments by kriging-based metamodeling and optimization,” J. Stat. Softw. 51(1), 155 (2012).Google Scholar
Bates, S. J., Sienz, J. and Toropov, V. V., “Formulation of the Optimal Latin Hypercube Design of Experiments Using a Permutation Genetic Algorithm,” AIAA, vol. 2011 (2004) pp 17.Google Scholar
Mallet, A., A guide to robotpkg (2017). Available at http://robotpkg.openrobots.org/robotpkg/README.html.Google Scholar
Pontzer, H., Raichlen, D. A. and Rodman, P. S., “Bipedal and quadrupedal locomotion in chimpanzees,” J. Hum. Evol. 66(1), 6482 (2014).CrossRefGoogle ScholarPubMed
Schmitt, D., “Insights into the evolution of human bipedalism from experimental studies of humans and other primates,” J. Exp. Biol. 206(9), 14371448 (2003).CrossRefGoogle ScholarPubMed
Kramer, P. A. and Eck, G. G., “Locomotor energetics and leg length in hominid bipedality,” J. Hum. Evol. 38(5), 651666 (2000).CrossRefGoogle ScholarPubMed
Hirasaki, E., Ogihara, N., Hamada, Y., Kumakura, H. and Nakatsukasa, M., “Do highly trained monkeys walk like humans? A kinematic study of bipedal locomotion in bipedally trained Japanese macaques,” J. Hum. Evol. 46(6), 739750 (2004).CrossRefGoogle ScholarPubMed
Nakatsukasa, M., Hirasaki, E. and Ogihara, N., “Energy expenditure of bipedal walking is higher than that of quadrupedal walking in Japanese macaques,” Am. J. Phys. Anthropol. Off. Publ. Am. Assoc. Phys. Anthropol. 131(1), 3337 (2006).CrossRefGoogle ScholarPubMed