Free Access
Volume 25, 2019
Article Number 81
Number of page(s) 29
Published online 19 December 2019
  1. Y. Baudoin and M.K. Habib, Using Robots in Hazardous Environments: Landmine Detection, De-Mining and Other Applications. Woodhead Publishing Limited (2011). [CrossRef] [Google Scholar]
  2. P. Agarwal, Pei-Hsin Kuo, R.R. Neptune and A.D. Deshpande, A novel framework for virtual prototyping of rehabilitation exoskeletons. IEEE International Conference on Rehabilitation Robotics (2013). [Google Scholar]
  3. B. Dellon and Y. Matsuoka, Prosthetics, Exoskeletons, and Rehabilitation. IEEE Robotics and Automation Magazine (2007). [Google Scholar]
  4. Wu Guorong and W. Wei, Application of human-machine interaction in toy design. Information Technology and Artificial Intelligence Conference (ITAIC) (2011). [Google Scholar]
  5. M. Cefalo and G. Oriolo, Task-Constrained Motion Planning for Underactuated Robots. IEEE International Conference on Robotics and Automation (ICRA). Washington (2015). [Google Scholar]
  6. B. d’Andra-Novel and S. Thorel, Control of non holonomic or under-actuated mechanical systems:The examples of the unicycle robot and the slider. ESAIM: COCV (2016). [Google Scholar]
  7. A. Mohammadi, M. Maggiore and L. Consolini, On the Lagrangian structure of reduced dynamics under virtual holonomic constraints. ESAIM: COCV (2016). [Google Scholar]
  8. R. Lecaros and L. Rosier, Control of underwater vehicles in inviscid fluids. ESAIM: COCV 20 (2014) 662–703. [CrossRef] [EDP Sciences] [Google Scholar]
  9. E.R. Westervelt, J.W. Grizzle, C. Chevallereau, Jun Ho Choi and B. Morris, Feedback Control of Dynamic Bipedal Robot Locomotion. CRC Press, Taylor and Francis Group (2007). [Google Scholar]
  10. N. Sugimoto and J. Morimoto, Phase-dependent Trajectory Optimization for CPG-based Biped Walking Using Path Integral Reinforcement Learning. 11th IEEE-RAS International Conference on Humanoid Robots, Bled, Slovenia (2011). [Google Scholar]
  11. J. Yu, M. Tan, J. Chen and J. Zhang, A Survey on CPG-Inspired Control Models and System Implementation. IEEE Transactions on Neural Networks and Learning Systems 25 (2014) 441–455. [CrossRef] [PubMed] [Google Scholar]
  12. S. Kajita, F. Kanehiro, K. Kaneko, K. Fujiwara, K. Yokoi and H. Hirukawa, A realtime pattern generator for biped walking, In Proc. of the 2002 IEEE International Conference on Robotics and Automation. Washington, D.C. (2002) 317. [Google Scholar]
  13. S. Kajita, F. Kanehiro, K. Kaneko, K. Yokoi, and H. Hirukawa, The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation, In Proc. of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Maui, HI (2001) 23946. [Google Scholar]
  14. M. Vukobratovic, B. Borovac, D. Surla and D. Stokic, Biped Locomotion. Springer-Verlag, Berlin (1990). [CrossRef] [Google Scholar]
  15. M. Vukobratovic and B. Borovac, Zero-moment point–thirty five years of its life. International Journal of Humanoid Robotics 1 (2004) 15773. [CrossRef] [Google Scholar]
  16. K. Hirai, M. Hirose, Y. Haikawa and T. Takenake, The development of Honda humanoid robot, In Proc. of the 1998 IEEE International Conference on Robotics and Automation. Leuven, Belgium (1998) 132126. [Google Scholar]
  17. R.D. Gregg, Timothy Bretl and M.W. Spong, Asymptotically Stable Gait Primitives for Planning Dynamic Bipedal Locomotion in Three Dimensions, 2010 IEEE International Conference on Robotics and Automation, Anchorage, Alaska, USA (2010). [Google Scholar]
  18. A. Goswami, Postural stability of biped robots and the foot-rotation indicator (FRI) point. International Journal of Robotics Research 18 (1999) 52333. [Google Scholar]
  19. Y. Hurmuzlu, Dynamics of bipedal gait Part 1: objective functions and the contact event of a planar five-link biped. J. Appl. Mechan. 60 (1993) 3316. [Google Scholar]
  20. Y. Hurmuzlu, Dynamics of bipedal gait Part 2: stability analysis of a planar five-link biped. J. Applied Mechanics 60 (1993) 33743. [Google Scholar]
  21. J.W. Grizzle, G. Abba and F. Plestan, Proving asymptotic stability of a walking cycle for a five DOF biped robot model. In Proc. of the 1999. Int. Conf. on Climbing and Walking Robots (1999) 69–81. [Google Scholar]
  22. J.W. Grizzle, G. Abba and F. Plestan, Asymptotically stable walking for biped robots: Analysis via systems with impulse effects. IEEE Transactions on Automatic Control 46 (2001) 51–64. [Google Scholar]
  23. J.W. Grizzle, F. Plestan and G. Abba, Poincares method for systems with impulse effects: Application to mechanical biped locomotion, In Proc. of the 1999 IEEE International Conference on Decision and Control, Phoenix, AZ (1999). [Google Scholar]
  24. E.R. Westervelt, G. Buche and J.W. Grizzle, Experimental validation of a framework for the design of controllers that induce stable walking in planar bipeds. Int. J. Robotics Res. 23 (2004) 5592. [CrossRef] [Google Scholar]
  25. E.R. Westervelt, G. Buche and J.W. Grizzle, Inducing dynamically stable walking in an underactuated prototype planar biped, In Proc. of the 2004 IEEE International Conference on Robotics and Automation, New Orleans, LA (2004) 42349. [Google Scholar]
  26. E.R. Westervelt, J.W. Grizzle and C. Canudas, Switching and PI control of walking motions of planar biped walkers. IEEE Trans. Automatic Control 48 (2003) 30812. [Google Scholar]
  27. C. Chevallereau, E.R. Westervelt and J.W. Grizzle, Asymptotically stable running for a five-link, four-actuator, planar bipedal robot. Int. J. Robotics Res. 24 (2005) 431–464. [CrossRef] [Google Scholar]
  28. E.R. Westervelt, J.W. Grizzle and D.E. Koditschek, Hybrid zero dynamics of planar biped walkers. IEEE Trans. Automatic Control 48 (2003) 42–56. [CrossRef] [MathSciNet] [Google Scholar]
  29. C. Chevallereau, J. Grizzle and C.-L. Shih, Asymptotically stable walking of a five-link underactuated 3-D bipedal robot. Robotics, IEEE Trans. 25 (2009) 37–50. [CrossRef] [Google Scholar]
  30. C. Chevallereau, G. Abba, Y. Aoustin, F. Plestan, E.R. Westervelt, C. Canudas-de-Wit and J.W. Grizzle, RABBIT: A Testbed for Advanced Control Theory, IEEE Control Systems Magazine, Paper number CSM-02-038, Revision June 8 (2003). [Google Scholar]
  31. E.A. Theodorou, J. Buchli and S. Schaal, A Generalized Path Integral Control Approach to Reinforcement Learning. J. Machine Learning Res. 11 (2010) 3137–3181. [Google Scholar]
  32. J. Buchli, F. Stulp, E. Theodorou and S. Schaal, Learning variable impedance control. Int. J. Robot. Res. 30 (2011) 820–833. [CrossRef] [Google Scholar]
  33. F. Stulp, E. Theodorou, M. Kalakrishnan, P. Pastor, L. Righetti and S. Schaal, Learning Motion Primitive Goals for Robust Manipulation. IEEE/RSJ International Conference on Intelligent Robots and Systems (2011). [Google Scholar]
  34. F. Stulp and O. Sigaud, Policy improvement methods: Between blackbox optimization and episodic reinforcement learning, in Journees Francophones sur la Planification, la Decision et l’Apprentissage pour la conduite de systemes (JFPDA) (2012). [Google Scholar]
  35. R. J. Williams, Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine Learning (1992). [Google Scholar]
  36. Peters and S. Schaal, Reinforcement learning of motor skills with policy gradients. Neural Networks 21 (2008) 68297. [CrossRef] [Google Scholar]
  37. J. Baxterand P.L. Bartlett, Infinite-horizon policy-gradient estimation. J. Artificial Intell. Res. Arch. 15 (2001) 3190–350. [Google Scholar]
  38. R.S. Sutton, D. McAllester, S. Singh and Y. Mansour, Policy gradient methods for reinforcement learning with function approximation, In Vol. 12 of Advances in Neural Information Processing Systems. MIT Press (2000) 1057–1063. [Google Scholar]
  39. J. Peters and S. Schaal, Natural actor critic, Neurocomputing (2008b). [PubMed] [Google Scholar]
  40. J. Koeber and J. Peters, Policy search for motor primitives, In Vol. 21 of Advances in Neural Information Processing Systems. (NIPS 2008). Vancouver, BC, Cambridge, MA: MIT Press (2008) 297–304. [Google Scholar]
  41. A.J. Ijspeert, J. Nakanishi, H. Homann, P. Pastor and S. Schaal, Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors. Neural Comput. 25 (2013) 328–373. [Google Scholar]
  42. R.F. Stengel, Optimal Control and Estimation, Dover books on advanced mathematics. Dover Publications, New York (1994). [Google Scholar]
  43. F. Stulp and O. Sigaud, Path Integral Policy Improvement with Covariance Matrix Adaptation, 29 th International Conference on Machine Learning, Edinburgh, Scotland, UK (2012). [Google Scholar]
  44. K. Akbari Hamed, B.G. Buss and J.W. Grizzle, Exponentially stabilizing continuous-time controllers for periodic orbits of hybrid systems: Application to bipedal locomotion with ground height variations. To appear in: Int. J. Robotics Res. (2015). [Google Scholar]
  45. K. Akbari Hamed and J.W. Grizzle, Event-Based Stabilization of Periodic Orbits for Underactuated 3-D Bipedal Robots With Left-Right Symmetry. IEEE Trans. Robotics 30 (2014) 365–381. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.