[1]
Juhász, Z., & Zelei, A. (2013). Analysis of worm-like locomotion. Mechanical Engineering, 57(2), 59-64.
DOI: 10.3311/ppme.7047
Google Scholar
[2]
Yamashita, A., Matsui, K., Kawanishi, R., Kaneko, T., Murakami, T., Omori, H., .. & Asama, H. (2011, December). Self-localization and 3-D model construction of pipe by earthworm robot equipped with omni-directional rangefinder. In Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on (pp.1017-1023.
DOI: 10.1109/robio.2011.6181421
Google Scholar
[3]
Wang, Y. K., Song, C. N., Wang, Z. L., Guo, C., & Tan, Q. Y. (2011). A SMA Actuated Earthworm-Like Robot. In Intelligent Computing and Information Science (pp.619-624). Springer Berlin Heidelberg.
DOI: 10.1007/978-3-642-18134-4_98
Google Scholar
[4]
Bodnicki, M., & Kamiński, D. (2014). In-pipe Microrobot Driven by SMA Elements. In Mechatronics 2013 (pp.527-533). Springer International Publishing.
DOI: 10.1007/978-3-319-02294-9_67
Google Scholar
[5]
Zhou, M., Tao, Y., Cheng, L., Liu, W. T., & Fu, X. (2013). A Biomimetic Earthworm-Like Micro Robot Using Nut-Type Piezoelectric Motor. In Intelligent Robotics and Applications (pp.129-135). Springer Berlin Heidelberg.
DOI: 10.1007/978-3-642-40852-6_15
Google Scholar
[6]
Zarrouk, D., Sharf, I., & Shoham, M. (2010, May). Analysis of earthworm-like robotic locomotion on compliant surfaces. In Robotics and Automation (ICRA)s, 2010 IEEE International Conference on (pp.1574-1579). IEEE.
DOI: 10.1109/robot.2010.5509846
Google Scholar
[7]
Zarrouk, D., Sharf, I., & Shoham, M. (2011). Analysis of wormlike robotic locomotion on compliant surfaces. IEEE Transactions on Biomedical Engineering, 58(2), 301-309.
DOI: 10.1109/tbme.2010.2066274
Google Scholar
[8]
Zarrouk, D., Sharf, I., & Shoham, M. (2012, May). Experimental validation of locomotion efficiency of worm-like robots and contact compliance. In Robotics and Automation (ICRA), 2012 IEEE International Conference on (pp.5080-5085). IEEE.
DOI: 10.1109/icra.2012.6224782
Google Scholar
[9]
Zarrouk, D., & Shoham, M. (2013, May). Energy requirements of inchworm crawling on a flexible surface and comparison to earthworm crawling. In Robotics and Automation (ICRA), 2013 IEEE International Conference on (pp.3342-3347). IEEE.
DOI: 10.1109/icra.2013.6631043
Google Scholar
[10]
Ghanbari, A., Rostami, A., Noorani, S. M. R. S., & Fakhrabadi, M. M. S. (2008). Modeling and simulation of inchworm mode locomotion. In Intelligent Robotics and Applications (pp.617-624). Springer Berlin Heidelberg.
DOI: 10.1007/978-3-540-88513-9_66
Google Scholar
[11]
Ghanbari, A., & Noorani, S. M. R. S. (2011). Optimal trajectory planning for design of a crawling gait in a robot using genetic algorithm. International Journal of Advanced Robotic Systems, 8(1), 29-36.
DOI: 10.5772/10526
Google Scholar
[12]
Kim, S., Hawkes, E., Cho, K., Joldaz, M., Foleyz, J., & Wood, R. (2009, October). Micro artificial muscle fiber using NiTi spring for soft robotics. In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on (pp.2228-2234.
DOI: 10.1109/iros.2009.5354178
Google Scholar
[13]
Seok, S., Onal, C. D., Cho, K. J., Wood, R. J., Rus, D., & Kim, S. (2013). Meshworm: a peristaltic soft robot with antagonistic nickel titanium coil actuators. Mechatronics, IEEE/ASME Transactions on, 18(5), 1485-1497.
DOI: 10.1109/tmech.2012.2204070
Google Scholar
[14]
Onal, C. D., Wood, R. J., & Rus, D. (2011, May). Towards printable robotics: Origami-inspired planar fabrication of three-dimensional mechanisms. In Robotics and Automation (ICRA), 2011 IEEE International Conference on (pp.4608-4613). IEEE.
DOI: 10.1109/icra.2011.5980139
Google Scholar
[15]
Onal, C. D., Wood, R. J., & Rus, D. (2013). An origami-inspired approach to worm robots. Mechatronics, IEEE/ASME Transactions on, 18(2), 430-438.
DOI: 10.1109/tmech.2012.2210239
Google Scholar
[16]
Ouyang, P. R., Zhang, W. J., & Wu, F. X. (2002).
Google Scholar
[17]
Ghorbel, F. H., Chételat, O., Gunawardana, R., & Longchamp, R. (2000). Modeling and set point control of closed-chain mechanisms: theory and experiment. Control Systems Technology, IEEE Transactions on, 8(5), 801-815.
DOI: 10.1109/87.865853
Google Scholar
[18]
Wu, F. X., Zhang, W. J., Li, Q., & Ouyang, P. R. (2002). Integrated design and PD control of high-speed closed-loop mechanisms. Journal of dynamic systems, measurement, and control, 124(4), 522-528.
DOI: 10.1115/1.1513179
Google Scholar
[19]
Cheng, H., Yiu, Y. K., & Li, Z. (2003). Dynamics and control of redundantly actuated parallel manipulators. Mechatronics, IEEE/ASME Transactions on, 8(4), 483-491.
DOI: 10.1109/tmech.2003.820006
Google Scholar
[20]
Codourey, A. (1998). Dynamic modeling of parallel robots for computed-torque control implementation. The International Journal of Robotics Research, 17(12), 1325-1336.
DOI: 10.1177/027836499801701205
Google Scholar
[21]
Davliakos, I., & Papadopoulos, E. (2008). Model-based control of a 6-dof electrohydraulic Stewart–Gough platform. Mechanism and machine theory, 43(11), 1385-1400.
DOI: 10.1016/j.mechmachtheory.2007.12.002
Google Scholar
[22]
Paccot, F., Lemoine, P., Andreff, N., Chablat, D., & Martinet, P. (2008, May). A vision-based computed torque control for parallel kinematic machines. In Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on (pp.1556-1561.
DOI: 10.1109/robot.2008.4543423
Google Scholar
[23]
Li, Q., & Wu, F. X. (2004). Control performance improvement of a parallel robot via the design for control approach. Mechatronics, 14(8), 947-964.
DOI: 10.1016/j.mechatronics.2004.04.002
Google Scholar
[24]
Shang, W., & Cong, S. (2009). Nonlinear computed torque control for a high-speed planar parallel manipulator. Mechatronics, 19(6), 987-992.
DOI: 10.1016/j.mechatronics.2009.04.002
Google Scholar
[25]
Yang, Z., Wu, J., & Mei, J. (2007). Motor-mechanism dynamic model based neural network optimized computed torque control of a high speed parallel manipulator. Mechatronics, 17(7), 381-390.
DOI: 10.1016/j.mechatronics.2007.04.009
Google Scholar
[26]
Yu, H. (2006). Modeling and control of hybrid machine systems—a five-bar mechanism case. International journal of automation and computing, 3(3), 235-243.
DOI: 10.1007/s11633-006-0235-1
Google Scholar
[27]
Yiu, Y. K., & Li, Z. X. (2003, July). PID and adaptive robust control of a 2-dof over-actuated parallel manipulator for tracking different trajectory. In Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on (Vol. 3, pp.1052-1057.
DOI: 10.1109/cira.2003.1222142
Google Scholar
[28]
Huang, D. S. (1998). The local minima-free condition of feedforward neural networks for outer-supervised learning. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 28(3), 477-480.
DOI: 10.1109/3477.678658
Google Scholar
[29]
Huang, D. S. (1997). The united adaptive learning algorithm for the link weights and shape parameter in RBFN for pattern recognition. International journal of pattern recognition and artificial intelligence, 11(06), 873-888.
DOI: 10.1142/s0218001497000391
Google Scholar
[30]
Moody, J., & Darken, C. J. (1989). Fast learning in networks of locally-tuned processing units. Neural computation, 1(2), 281-294.
DOI: 10.1162/neco.1989.1.2.281
Google Scholar
[31]
Zhang, D., & Lei, J. (2011). Kinematic analysis of a novel 3-DOF actuation redundant parallel manipulator using artificial intelligence approach. Robotics and Computer-Integrated Manufacturing, 27(1), 157-163.
DOI: 10.1016/j.rcim.2010.07.003
Google Scholar