Large-area tactile sensors based on the technique of electrical impedance tomography (EIT) has drawn considerable interest in human-robot interactions. However, due to the ill-posed condition, it is challenging to differentiate between the real contacts and the artifacts from the reconstructed image. To address this issue, a new method to select an optimal hyperparameter that tunes the amount of regularization is developed in the context of tactile sensing. The optimal hyperparameter is determined to be the minimum value to obtain a stabilized number of sub-regions in the reconstructed image. The proposed method not only guarantees a correct detection on the number of multiple contacts at the minimum amount of regularization, but also provides a proper range of hyperparameters. The optimal hyperparameter is found in a chair-shape relation with the boundary signal-to-noise ratio (SNR), by varying the noise level of the hardware in simulation. The optimal hyperparameter decreases significantly when the boundary SNR increases between 5~10 dB and 25~35 dB, and keeps almost unchanged when SNR is between 10~25 dB. The chair-shape relation also holds for contact conditions with varied intensities and sizes. Experimental validations on the proposed method are conducted on a compliant piezoresistive tactile sensor made of exfoliated graphite polymer composites. By varying the number of contacts in experiments, the relation between the optimal hyperparameter and the boundary SNR is consistent with the chair-shape curve. The investigation made in this work helps improve the performance of identifying multiple contacts from tactile sensors based on electrical impedance tomography.
Compliant tactile sensing has received increasing interests in human-robot interactions and soft robotic sensing. However, it is still challenging to achieve high sensing performance over an area with low wiring complexity. This paper is to implement and evaluate a soft, distributed sensor that is enabled by the technique of electrical impedance tomography (EIT), which allows areal sensing using only boundary measurements. To achieve mechanical compliance of the sensor, a functional natural rubber composites filled with exfoliated graphite (EG/NR) is fabricated by spray coating. Long-term stability of the sensing material is evaluated under cyclic tests, and a high gauge factor of 6.25 is obtained, which can be explained from the evolution of the micromorphology under strain. A continuous sensing area with a diameter of 12 cm is prepared, and 16 electrodes are attached along the periphery to implement distributed sensing. The performance of the sensor is characterized under indentation tests. Results show that the intensity sensitivity monotonically decreases with the distance to the boundary, and consistent response is obtained along all the radial directions, providing predictable performance over the sensing area.
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