An approach to optimise the critical sensor locations in one-dimensional novel distributive tactile surface to maximise performance

Sensors and Actuators, A: Physical

Volumn 105, Issue 1, 2003, Pages 47-54

  Tongpadungroda, P ^a   Rhysb, T D L ^b   Brettc, P N ^c  

^a KING MONGKUT'S UNIVERSITY OF TECHNOLOGY NORTH BANGKOK   (Thailand)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

^c ASTON UNIVERSITY   (United Kingdom)

Author keywords

Back propagation neural network; Distributive; Genetic algorithm; Optimisation; Principal component analysis; Tactile sensing

Indexed keywords

GENETIC ALGORITHMS; NEURAL NETWORKS; NONBIBLIOGRAPHIC RETRIEVAL SYSTEMS; PRINCIPAL COMPONENT ANALYSIS;

TACTILE SENSORS;

SENSORS;

EID: 0038321299     PISSN: 09244247     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0924-4247(03)00059-1     Document Type: Article

References (19)

1. Kistler, Force plate, http://www.kistler.com/, September 1999.
2. R.S. Fearing, Tactile sensing mechanism, Int. J. Robot. Res. 9 (3) (1990) 3-23.
3. G. Canepa, R. Petrigliano, M. Campanella, D. DeRossi, Detection of incipient object slippage by skin-like sensing and neural network processing, IEEE Trans. Syst. Man Cybernet. Part B: Cybernet. 28 (3) (1998) 348-356.
4. B. Eberman, J.K. Salisbury, Application of change detection to dynamic contact sensing, Int. J. Robot. Res. 13 (5) (1994) 369-394.
5. A.J. Harrison, P.J. Hillard, A moment-based technique for the automatic spatial alignment of plantar pressure data, Proc. Inst. Mech. Eng. Part H: J. Eng. Med. 214 (3) (2000) 257-264.
6. A. Caiti, G. Canepa, D. DeRossi, F. Germagnoli, G. Magnenes, T. Parisisni, Towards the realization of an artificial tactile system: fine-form discrimination by a tensorial tactile sensor array and neural inversion algorithms, IEEE Trans. Syst. Man Cybernet. 25 (6) (1995).
7. A. Leung, S. Payandeh, Application of adaptive neural network to localization of objects using pressure array transducer, Robotica 14 (4) (1996) 407-414.
8. E.G.M. Holweg, W. Jongkind, Object recognition using a tactile matrix sensor, in: Proceedings of the EURISCON'94 Advanced Manufacturing and Automation RES 1994, August 1994, Malaga, Spain, pp. 1379-1383.
9. R.E. Ellis, S.R. Ganeshan, S.J. Lederman, A tactile sensing-based on thin plate deformation, Robotica 12 (4) (1994) 343-351.
10. R.W.S. Stone, A distributive tactile sensing technique for soft deformable contact, University of Bristol, 1997.
11. R.S.W. Stone, P.N. Brett, A sensing technique for the measurement of tactile forces in the gripping of dough like material, Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 210 (3) (1996) 261-269.
12. B.S. Evans, P.N. Brett, Computer simulation of the deformation of dough-like materials in a parallel plate gripper, Proc. Inst. Mech. Eng. 210 (B) (1996) 119-126.
13. H. Demuth, M. Beale, Neural Network Toolbox Technical Manual, Math Works, Inc., Natick, MA, June 1992.
14. W.C. Young, Roark's Formulas for Stress and Strain, McGraw-Hill, Singapore, 1989.
15. C. Quo, W. Wu, D.L. Massart, C. Boucon, S. de-Jong, Feature selection in principal component analysis of analytical data, Chemom. Intell. Lab. Syst. 61 (1-2) (2002) 123-132.
16. A. Spalanzani, S.A. Selouani, Improving robustness of connectionist speech recognition systems by genetic algorithms, in: Proceedings of the 1999 International Conference on Information Intelligence and Systems, Cat. No. PR00446, 1999, pp. 415-422.
17. J.F. MacGregor, T. Kourti, Statistical process control of multivariate processes, Contr. Eng. Pract. 3 (3) (1995) 403-414.
18. J.B. Gomm, M. Weerasinghe, D. Williams, Diagnosis of process faults with neural networks and principal component analysis, Proc. Inst. Mech. Eng. Part E 214 (2) (2000) 131-143.
19. J.A. Nickerson, T.W. Sloan, Data reduction techniques and hypothesis testing for analysis of bench-marking data, Int. J. Prod. Res. 37 (8) (1999) 1717-1741.