Abstract
Tensegrity mobile robots have merits of high stiff-to-mass ratio and superior structural compliance, making them a hot research topic recently. In this work, a novel modular tensegrity mobile robot with multi-locomotion modes is proposed. Unlike the existing conventional tensegrity robots, the robot in this work has abundant deformation ability, and can achieve four locomotion modes in terms of earthworm-like, inchworm-like, tumbling and hybrid locomotion. Afterwards, motion planning of the four locomotion modes based on the kinematic model is implemented, and the driving law of the motors under each locomotion mode can be obtained. A prototype of the robot is developed, and experimental results show that the robot can effectively adjust to five types of terrains by the four locomotion modes (maximum velocity on flat ground 33.90 BL/min, minimum height of confined space 1.18 BH, maximum angle of slope 9°, maximum height of obstacle 0.55 BH and maximum width of gap 0.21 BL. BL and BH represent the body length and body height of the robot, respectively). This work provides a useful reference for the application of tensegrity structures in the field of multi-locomotion mobile robot.
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References
Sychterz, A.C., Smith, I.F.C.: Using dynamic measurements to detect and locate ruptured cables on a tensegrity structure. Eng. Struct. 173, 631–642 (2018)
Yang, S., Sultan, C.: Deployment of foldable tensegrity–membrane systems via transition between tensegrity configurations and tensegrity–membrane configurations. Int. J. Solids Struct. 160, 103119 (2019)
Feng, X.D., Miah, M.S., Ou, Y.W.: Dynamic behavior and vibration mitigation of a spatial tensegrity beam. Eng. Struct. 171, 1007–1016 (2018)
Wang, Y.F., Xu, X., Luo, Y.Z.: Minimal mass design of active tensegrity structures. Eng. Struct. 234, 111965 (2021)
Luo, J.L., Rdmunds, R., Rice, F., Agogino, A.M.: Tensegrity robot locomotion under limited sensory inputs via deep reinforcement learning. In: 2018 IEEE International Conference on Robotics and Automation, pp. 6260–5267. IEEE Press, Brisbance (2018)
Savin, S., Badr, A.A., Devitt, D., Fedorenko, R., Klimchik, A.: Mixed–integer–based path and morphing planning for a tensegrity drone. Appl. Sci. 12(11), 5588 (2022)
Liu, Y.X., Bi, Q., Yue, X.M., Wu, J., Yang, B., Li, Y.B.: A review on tensegrity structures–based robots. Mech. Mach. Theory 168, 104571 (2022)
Shah, D.S., et al.: Tensegrity robotics. Soft Robotics 9(4), 639–656 (2021)
Sabelhaus, A.P., et al.: System design and locomotion of SUPERball, an untethered tensegrity robot. In: 2015 IEEE International Conference on Robotics and Automation, pp. 1050–4729. IEEE Press, Seattle (2015)
Vespignani, M., Friesen, J.M., SunSpiral, V., Bruce, J.: Design of SUPERball v2, a compliant tensegrity robot for absorbing large impacts. In: Maciejewski, A.A., Okamura, A. (eds.) 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2865–2871. IEEE Press, Madrid (2018)
Kim, K., Agogino, A.K., Agogion, A.M.: Emergent form–finding for center of mass control of ball–shaped tensegrity robots (2015)
Kim, K., Agogino, A.K., Toghyan, A., Moon, D., Taneja, L., Agogino, A.M: Robust learning of tensegrity robot control for locomotion through form–finding. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5824–5831. IEEE Press, Hamburg (2016)
Chen, L.H., et al.: Soft spherical tensegrity robot design using rod–centered actuation and control. In: 2016 ASME International Design Engineering Technical Conference/Computer and Information in Engineering Conference (IDETC/CIE), vol. 9, p. 025001. ASME, Charlotte (2016)
Hao, S.Q., et al.: Configuration design and gait planning of a six-bar tensegrity robot. Appl. Sci. 12(22), 11845 (2022)
Littlefield, Z., Surovik, D., Vespignani, M., Bruce, J., Wang, W.F., Bekris, K.E.: Kinodynamic planning for spherical tensegrity locomotion with effective gait primitives. Int. J. Robot. Res. 38(12), 1442–1462 (2019)
Paul, C., Roberts, J.W., Lipson, H., Cuevas, F.J.V: Gait production in a tensegrity based robot. In: 12th International Conference on Advanced Robotics, pp.216–222. IEEE Press, Seattle (2005)
Rovira, A.G., Tur, J.M.M.: Control and simulation of a tensegrity–based mobile robot. Robot. Auton. Syst. 57(5), 526–535 (2009)
Luo, A., Wang, J.D., Liu, H.P.: Four–bar tensegrity robot based on ADAMS simulation. In: 2017 IEEE International Conference on Mechatronics and Automation (ICMA), pp.1463–1468. IEEE Press, Takamatsu (2017)
Chung, Y.S., Lee, J.H., Jang, J.H., Choi, H.R., Rodrigue, H.: Jumping tensegrity robot based on torsionally prestrained SMA Springs. ACS Appl. Mater. Interfaces. 11(43), 40793–40799 (2019)
Kim, K., et al.: Hopping and rolling locomotion with spherical tensegrity robots. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4369–4376. IEEE Press, Daejeon (2016)
Koizumi, Y., Shibata, M., Hirai, S.: Rolling tensegrity driven by pneumatic soft actuators. In: 2012 IEEE International Conference on Robotics and Automation, pp. 1988–1993. IEEE Press, Paul (2012)
Khazanov, M., Humphreys, B., Keat, W., Rieffel, J.: Exploiting dynamical complexity in a physical tensegrity robot to achieve locomotion. In: The Twelfth European Conference on Artificial Life, pp. 965–972. ASME, Sicily (2013)
Wang, Z.J., Li, K., He, Q.G., Cai, S.Q.: A light–powered ultralight tensegrity robot with high deformability and load capacity. Adv. Mater. 31(7), 1806849 (2019)
Paul, C., Valero–Cuevas, F.J., Lipson, H: Design and control of tensegrity robots for locomotion. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 22, pp. 944–957. IEEE Press, Edmonton (2005)
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This work is funded by National Natural Science Foundation of China (grants 52275028).
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Yang, Q., Yu, Z., Lian, B., Sun, T. (2023). A Modular Tensegrity Mobile Robot with Multi-locomotion Modes. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14267. Springer, Singapore. https://doi.org/10.1007/978-981-99-6483-3_27
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DOI: https://doi.org/10.1007/978-981-99-6483-3_27
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