Published 2023
| Version v1
Publication
Embedded Implementation of Signal Pre-processing for Tactile Sensing System
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Description
Smart tactile sensing system has been a subject of research in many
application domains such as prosthetics and robotics. Embedding signal pre-processing methods (i.e., filters) along with processing algorithms (i.e., machine
learning) into miniaturized electronic units enhance the extraction of high-bandwidth information (e.g., slippage detection). However, it is challenging due to the
high computational costs and the real time requirements. This paper proposes a
lightweight implementation of pre-processing method for multichannel tactile
sensing system. We targeted two filtering methods, Finite Impulse Response
(FIR) and Exponential Moving Average Filter (EMAF). The paper presents the
analysis of the implementation performance on hardware i.e., number of clock
cycles, execution time and touch detection accuracy. Experimental results show
that EMAF is more effective than FIR when it comes to the hardware complexity.
This means that the computational cost for implementing such pre-processing
filter is negligible and thus acceptable for time, and hardware constraint tactile
sensing system.
Additional details
Identifiers
- URL
- https://hdl.handle.net/11567/1098119
- URN
- urn:oai:iris.unige.it:11567/1098119