Abstract
Decoupling research on flexible tactile sensors play a very important role in the intelligent robot skin and tactile-sensing fields. In this paper, an efficient machine learning method based on the improved back-propagation (BP) algorithm is proposed to decouple the mapping relationship between the resistances of force-sensitive conductive pillars and three-dimensional forces for the 6 × 6 novel flexible tactile sensor array. Tactile-sensing principles and numerical experiments are analyzed. The tactile sensor array model accomplishes the decomposition of the force components by its delicate structure, and avoids direct interference among the electrodes of the sensor array. The force components loaded on the tactile sensor are decoupled with a very high precision from the resistance signal by the improved BP algorithm. The decoupling results show that the k-cross validation (k-CV) algorithm is a highly effective method to improve the decoupling precision of force components for the novel tactile sensor. The large dataset with the k-CV method obtains a better decoupling accuracy of the force components than the small dataset. All of the decoupling results are fairly good, and they indicate that the improved BP model with a strong non-linear approaching ability has an efficient and valid performance in decoupling force components for the tactile sensor.
Highlights
With the rapid developments of intelligent robots and tactile-sensing technology, soft and thin tactile sensors play a very important role in the intelligent robot skin field, as they can offer feedback information about external forces loaded on the robot skin
Based on the above analysis, this paper focuses on the study of the multi-dimensional information decoupling and the approximation of the high dimensional non-linear mapping relationship between the resistances signal and three-dimensional force components for a novel flexible tactile sensor array
Theoretical analysis and numerical experiments are conducted for the 6 × 6 flexible tactile sensor array
Summary
With the rapid developments of intelligent robots and tactile-sensing technology, soft and thin tactile sensors play a very important role in the intelligent robot skin field, as they can offer feedback information about external forces loaded on the robot skin. Tactile sensors can help robots recognize objects and forces loaded on to complete a variety of complex tasks. They can acquire lots of useful information—such as shapes, hardness, elasticity, and roughness—from the object and the surrounding environment. The sensitivity of tactile sensing is crucial for ensuring the safe and efficient interaction between robots and the environment; tactile sensor research plays an indispensable role in the bionic intelligent robot field. The design principle for tactile sensors developed with different tactile-sensing mechanisms mainly concentrate on piezoelectricity [1,2], capacitance [3,4,5,6], optical fiber [7,8,9], single-walled carbon nanotube [10] technology, and so forth. Some other studies have concentrated on the grasp control for specific environments by estimating the contact force [16,17], but paid less attention to the decoupling method for the force loaded on the sensor
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