A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Advanced Search
Volume 7 Issue 3
Apr.  2020

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 17.6, Top 3% (Q1)
    Google Scholar h5-index: 77， TOP 5
Turn off MathJax
Article Contents
Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2020  >  7(3): 745-751
Dong Zhang, Hao Yuan and Zhengcai Cao, "Environmental Adaptive Control of a Snake-like Robot With Variable Stiffness Actuators," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 745-751, May 2020. doi: 10.1109/JAS.2020.1003144
Citation: Dong Zhang, Hao Yuan and Zhengcai Cao, "Environmental Adaptive Control of a Snake-like Robot With Variable Stiffness Actuators," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 745-751, May 2020. doi: 10.1109/JAS.2020.1003144
shu

Environmental Adaptive Control of a Snake-like Robot With Variable Stiffness Actuators

doi: 10.1109/JAS.2020.1003144
Funds:  This work was supported by the National Natural Science Foundation of China (51575034), Beijing Leading Talents Program (Z191100006119031), Beijing Municipal Natural Science Foundation (3202022), National Key Research and Development Program of China (2018YFB1304600), and the State Key Laboratory of Robotics of China (2018-O15)
More Information
    Abstract
  • This work investigates adaptive stiffness control and motion optimization of a snake-like robot with variable stiffness actuators. The robot can vary its stiffness by controlling magneto-rheological fluid (MRF) around actuators. In order to improve the robot’s physical stability in complex environments, this work proposes an adaptive stiffness control strategy. This strategy is also useful for the robot to avoid disturbing caused by emergency situations such as collisions. In addition, to obtain optimal stiffness and reduce energy consumption, both torques of actuators and stiffness of the MRF braker are considered and optimized by using an evolutionary optimization algorithm. Simulations and experiments are conducted to verify the proposed adaptive stiffness control and optimization methods for a variable stiffness snake-like robots.

     

    • FullText(HTML)
  • loading
    • References(32)
  • [1]
    R. Bogue, “Snake robots: a review of research, products and applications,” Industrial Robot, vol. 41, no. 3, pp. 253–258, 2014. doi: 10.1108/IR-02-2014-0309
    [2]
    H. Ohno and S. Hirose, “Design of slim slime robot and its gait of locomotion,” in Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 707–715, 2001.
    [3]
    A. Crespi, A. Badertscher, A. Guignard, and A. J. Ijspeert, “AmphiBot I: an amphibious snake-like robot,” Mechatronics, vol. 50, no. 4, pp. 163–175, 2005. doi: 10.1016/j.robot.2004.09.015
    [4]
    H. Kimura and S. Hirose, “Development of Genbu: active wheel passive joint articulated mobile robot,” in Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 823–828, 2002.
    [5]
    H. Yamada and S. Hirose, “Development of practical 3-dimensional active cord mechanism ACM-R4,” J. Robotics &Mechatronics, vol. 18, no. 3, pp. 305–311, 2006.
    [6]
    S. Sugita, K. Ogami, G. Michele, S. Hirose, and K. Takita, “A study on the mechanism and locomotion strategy for new snake-like robot active cord mechanism Slime model 1 ACM-S1,” J. Robotics &Mechatronics, vol. 20, no. 2, pp. 302–310, 2008.
    [7]
    P. Liljebäck, K. Pettersen, Ø. Stavdahl, and J. Gravdahl, “Controllability and stability analysis of planar snake robot locomotion,” IEEE Trans. Autom. Control, vol. 56, no. 6, pp. 1365–1380, 2011. doi: 10.1109/TAC.2010.2088830
    [8]
    X. D. Wu and S. G. Ma, “Adaptive creeping locomotion of a CPG-controlled snake-like robot to environment change,” Autonomous Robots, vol. 28, no. 3, pp. 283–294, 2010. doi: 10.1007/s10514-009-9168-1
    [9]
    E. Kelasidi, M. Jesmani, K. Y. Pettersen, and J. T. Gravdahl, “Multiobjective optimization for efficient motion of underwater snake robots,” Artificial Life &Robotics, vol. 21, no. 4, pp. 1–12, 2016.
    [10]
    Z. C. Cao, Q. Xiao, R. Huang, and M. C. Zhou, “Robust neuro-optimal control of underactuated snake robots with experience replay,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 1, pp. 208–217, 2018. doi: 10.1109/TNNLS.2017.2768820
    [11]
    A. A. Transeth, R. I. Leine, and K. Y. Pettersen, “3-D snake robot motion: nonsmooth modeling, simulations, and experiments,” IEEE Trans. Robotics, vol. 24, no. 2, pp. 361–376, 2008. doi: 10.1109/TRO.2008.917003
    [12]
    R. Hatton and H. Choset, “Sidewinding on slopes,” in Proc. IEEE Int. Conf. on Robotics and Autom., pp. 691–696, 2010.
    [13]
    H. Marvi, C. H. Gong, N. Gravish, H. Astley, M. Travers, R. L. Hatton, J. R. Mendelson, H. Choset, D. L. Hu, and D. I. Goldman, “Sidewinding with minimal slip: snake and robot ascent of sandy slopes,” Science, vol. 346, no. 6206, pp. 224–229, 2014. doi: 10.1126/science.1255718
    [14]
    J. Whitman, N. Zevallos, M. Travers, and H. Choset, “Snake robot urban search after the 2017 mexico city earthquake,” in Proc. IEEE Int. Symposium on Safety, Security, and Rescue Robotics, pp. 2475–8426, 2018.
    [15]
    P. U. Chavan, M. Murugan, E. V. Unnikkannan, and A. Singh, “Modular snake robot with mapping and navigation: urban search and rescue (USAR) robot,” in Proc. Int. Conf. on Computing Communication Control & Automation, 2015. doi: 10.1109/ICCUBEA.2015.110
    [16]
    M. Okui, S. Iikawa, Y. Yamada, and T. Nakamura, “Variable viscoelastic joint system and its application to exoskeleton,” in Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 3897–3902, 2017.
    [17]
    Y. W. Liu, X. G. Liu, Z. Q. Yuan, and J. G. Liu, “Design and analysis of spring parallel variable stiffness actuator based on antagonistic principle,” Mechanism and Machine Theory, vol. 140, pp. 44–58, 2019. doi: 10.1016/j.mechmachtheory.2019.05.016
    [18]
    Z. Zhang, G. L. Yang, and H. Y. Song, “Inverse kinematics of modular cable-driven snake-like robots with flexible backbones,” in Proc. 5th IEEE Robotics, Autom. and Mechatronics, pp. 41–461, 2011.
    [19]
    J. Sheard, R. Draper, and M. Troughton, “Soft robotic snake with variable stiffness actuation,” in Proc. Towards Autonomous Robotic Systems, pp. 363–377, 2017.
    [20]
    J. W. Sohn, J. Jeon, Q. H. Nguyen, and S. B. Choi, “Optimal design of disctype magneto-rheological brake for mid-sized motorcycle: experimental evaluation,” Smart Materials &Structures, vol. 24, no. 8, pp. 1–11, 2015.
    [21]
    A. Calanca, R. Muradore, and P. Fiorini, “A review of algorithms for compliant control of stiff and fixed-compliance robots,” Smart Materials &Structures, vol. 21, no. 2, pp. 613–624, 2016.
    [22]
    P. Liljebäck, K. Y. Pettersen, Ø. Stavdahl, and J. T. Gravdahl, “Compliant control of the body shape of snake robots,” in Proc. IEEE Int. Conf. on Robotics & Autom., pp. 4549–4555, 2014.
    [23]
    M. Vespignani, K. Melo, and M. Mutlu, “Compliant snake robot locomotion on horizontal pipes,” in Proc. IEEE Int. Symposium on Safety, pp. 370–375, 2016.
    [24]
    A. Kakogawa, S. Jeon, and S. G. Ma, “Stiffness design of a resonancebased planar snake robot with parallel elastic actuators,” IEEE Robotics and Autom. Letters, vol. 3, no. 2, pp. 1284–1291, 2018. doi: 10.1109/LRA.2018.2797261
    [25]
    Z. C. Cao, D. Zhang, H. Biao, and J. G. Liu, “Adaptive path following and locomotion optimization of snake-like robot controlled by the central pattern generator,” Complexity, vol. 2019, pp. 8030374, 2019.
    [26]
    G. F. Qiao, X. L. Wen, G. M. Song, and Q. Wan, “Effects of the compliant intervertebral discs in the snake-like robots: a simulation study,” in Proc. IEEE Int. Conf. on Robotics & Biomimetics, pp. 813–818, 2017.
    [27]
    J. Whitman, F. Ruscelli, and M. Travers, “Shape-based compliant control with variable coordination centralization on a snake robot,” in Proc. IEEE Conf. on Decision & Control, pp. 5165–5170, 2016.
    [28]
    J. K. Li, B. Hu, P. Geng, and Z. C. Cao, “Variable stiffness mechanism design and analysis for a snake-like robot,” in Proc. IEEE Int. Conf. on Robotics & Biomimetics, pp. 331–336, 2018.
    [29]
    X. Guo, S. G. Ma, B. Li, and M. H. Wang, “Locomotion control of a snake-like robot based on velocity disturbance,” in Proc. IEEE Int. Conf. on Robotics & Biomimetics, pp. 582–587, 2014.
    [30]
    Q. F. Zhang and H. Li, “MOEA/D: a multiobjective evolutionary algorithm based on decomposition,” IEEE Trans. Evolutionary Computation, vol. 11, no. 6, pp. 712–731, 2008.
    [31]
    Q. Kang, X. Y. Song, M. C. Zhou, and L. Li, “A collaborative resource allocation strategy for decomposition-based multi objective evolutionary algorithms,” IEEE Trans. Systems,Man,and Cybernetics:Systems, vol. 49, no. 12, pp. 2416–2423, 2019.
    [32]
    Q. L. Peng, M. C. Zhou, Q. He, Y. N. Xia, C. R. Wu, and S. G. Deng, “Multi-objective optimization for location prediction of mobile devices in sensor-based applications,” IEEE Access, vol. 6, pp. 77123–77132, 2018. doi: 10.1109/ACCESS.2018.2869897
    • Related Articles
    • Supplements(0)

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(12)  / Tables(2)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (1674) PDF downloads(97) Cited by()

    Highlights

    • A snake-like robot with variable stiffness actuators is designed. The robot can vary its stiffness by controlling magnetorheological fluid around its actuators.
    • An adaptive stiffness control strategy is proposed to improve the robot’s physical stability in complex environments. This strategy is also useful for the robot to avoid disturbing caused by emergency situations such as collisions.
    • Torques of actuators and stiffness of the magnetorheological fluid braker are considered and optimized by using an evolutionary optimization algorithm to obtain optimal stiffness and reduce energy consumption.

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return