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Pubmed for Handhelds
PUBMED FOR HANDHELDS
Journal Abstract Search
137 related items for PubMed ID: 15503506
1. Online learning of virtual impedance parameters in non-contact impedance control using neural networks. Tsuji T, Terauchi M, Tanaka Y. IEEE Trans Syst Man Cybern B Cybern; 2004 Oct; 34(5):2112-8. PubMed ID: 15503506 [Abstract] [Full Text] [Related]
2. Online tuning of fuzzy inference systems using dynamic fuzzy Q-learning. Er MJ, Deng C. IEEE Trans Syst Man Cybern B Cybern; 2004 Jun; 34(3):1478-89. PubMed ID: 15484918 [Abstract] [Full Text] [Related]
3. Neural network learning of robot arm impedance in operational space. Tsuji T, Ito K, Morasso PG. IEEE Trans Syst Man Cybern B Cybern; 1996 Jun; 26(2):290-8. PubMed ID: 18263030 [Abstract] [Full Text] [Related]
4. Constrained motion control of flexible robot manipulators based on recurrent neural networks. Tian L, Wang J, Mao Z. IEEE Trans Syst Man Cybern B Cybern; 2004 Jun; 34(3):1541-52. PubMed ID: 15484923 [Abstract] [Full Text] [Related]
5. Perception control with improved expectation learning through multilayered neural networks. Guirnaldo S, Watanabe K, Izumi K, Kiguchi K. IEEE Trans Syst Man Cybern B Cybern; 2004 Jun; 34(3):1582-7. PubMed ID: 15484927 [No Abstract] [Full Text] [Related]
6. Adaptive fuzzy neural network control design via a T-S fuzzy model for a robot manipulator including actuator dynamics. Wai RJ, Yang ZW. IEEE Trans Syst Man Cybern B Cybern; 2008 Oct; 38(5):1326-46. PubMed ID: 18784015 [Abstract] [Full Text] [Related]
7. Impedance learning for robotic contact tasks using natural actor-critic algorithm. Kim B, Park J, Park S, Kang S. IEEE Trans Syst Man Cybern B Cybern; 2010 Apr; 40(2):433-43. PubMed ID: 19696001 [Abstract] [Full Text] [Related]
8. Body schema learning for robotic manipulators from visual self-perception. Sturm J, Plagemann C, Burgard W. J Physiol Paris; 2009 Apr; 103(3-5):220-31. PubMed ID: 19665561 [Abstract] [Full Text] [Related]
9. Global convergence of online BP training with dynamic learning rate. Zhang R, Xu ZB, Huang GB, Wang D. IEEE Trans Neural Netw Learn Syst; 2012 Feb; 23(2):330-41. PubMed ID: 24808511 [Abstract] [Full Text] [Related]
10. A new performance index for the repetitive motion of mobile manipulators. Xiao L, Zhang Y. IEEE Trans Cybern; 2014 Feb; 44(2):280-92. PubMed ID: 23757549 [Abstract] [Full Text] [Related]
13. Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks. Li Z, Ge SS, Liu S. IEEE Trans Neural Netw Learn Syst; 2014 Aug; 25(8):1460-73. PubMed ID: 25050944 [Abstract] [Full Text] [Related]
14. A primal-dual neural network for online resolving constrained kinematic redundancy in robot motion control. Xia YS, Feng G, Wang J. IEEE Trans Syst Man Cybern B Cybern; 2005 Feb; 35(1):54-64. PubMed ID: 15719933 [Abstract] [Full Text] [Related]
16. Brain-machine interface control of a manipulator using small-world neural network and shared control strategy. Li T, Hong J, Zhang J, Guo F. J Neurosci Methods; 2014 Mar 15; 224():26-38. PubMed ID: 24333753 [Abstract] [Full Text] [Related]
17. Advanced Interval Type-2 Fuzzy Sliding Mode Control for Robot Manipulator. Hwang JH, Kang YC, Park JW, Kim DW. Comput Intell Neurosci; 2017 Mar 15; 2017():9640849. PubMed ID: 28280505 [Abstract] [Full Text] [Related]
18. Comparison of some modeling and control issues for a flexible two link manipulator. Zhang X, Xu W, Nair SS. ISA Trans; 2004 Oct 15; 43(4):509-25. PubMed ID: 15535391 [Abstract] [Full Text] [Related]
19. Nonlinear visual mapping model for 3-D visual tracking with uncalibrated eye-in-hand robotic system. Su J, Xi Y, Hanebeck UD, Schmidt G. IEEE Trans Syst Man Cybern B Cybern; 2004 Feb 15; 34(1):652-9. PubMed ID: 15369103 [Abstract] [Full Text] [Related]
20. Grounding vision through experimental manipulation. Fitzpatrick P, Metta G. Philos Trans A Math Phys Eng Sci; 2003 Oct 15; 361(1811):2165-85. PubMed ID: 14599314 [Abstract] [Full Text] [Related] Page: [Next] [New Search]