Adaptive Optimal Measurement Algorithm for ERT-based Large-area Tactile Sensors

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Electrical resistance tomography (ERT) is an inferential imaging technique that has shown promising results for enabling large-area tactile sensors constructed from a piezoresistive sheet. The performance of such sensors is improved by increasing the number of electrodes, but the number of measurements and the computational cost also increase. In this paper, we propose a new measurement algorithm for ERT-based tactile sensors: it adaptively changes the measurement pattern to be optimal for the present external stimulus. Regions of normal pressure are first detected by a base measurement pattern that maximizes the distinguishability of local conductivity changes. When a new contact is detected, a set of local patterns is selectively recruited near the pressed region to acquire more detailed information. For fast and parallel execution, the proposed algorithm is implemented with a field-programmable gate array (FPGA). It is validated through indentation experiments on an ERT-based sensor that has 32 electrodes. The optimized base pattern of 100 measurements enabled a frame rate five times faster than before. Transmitting only detected contact events reduced the idle data rate to 0.5% of its original value. The pattern adapted to new contacts with a latency of only 80 microseconds and an accuracy of 99.5%, enabling efficient, high-quality real-time reconstruction of complex multi-contact conditions.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2022-02
Language
English
Article Type
Article
Citation

IEEE-ASME TRANSACTIONS ON MECHATRONICS, v.27, no.1, pp.304 - 314

ISSN
1083-4435
DOI
10.1109/tmech.2021.3063414
URI
http://hdl.handle.net/10203/294798
Appears in Collection
ME-Journal Papers(저널논문)
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