Shape estimation with tactile sensors: a radial basis functions approach
1992
Fine-form detection and discrimination of an object in contact with a skin-like tactile sensor is a basic feature in machine taction for perceptual, grasping and manipulation tasks. The inversion of tactile data in the form of normal and shear stress components in order to recover the contact shape and contact radius in the class of axisymmetry indenters gives rise to a nonlinear inverse problem which must be conceptually solved by using regularization techniques. Radial basis functions networks are used to solve this problem owing to their direct connection with regularization and approximate theory. Simulation results show the effectiveness of the proposed approach even with large noise added to the data. >
Keywords:
- Approximation theory
- Mathematical optimization
- Inverse problem
- Control theory
- Radial basis function
- Regularization (mathematics)
- Tactile sensor
- Radial basis function network
- Shear stress
- Nonlinear system
- Mathematics
- approximate theory
- contact radius
- Computer vision
- Algorithm
- Inversion (meteorology)
- Computer science
- nonlinear inverse problem
- Artificial intelligence
- Correction
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