MEMS-CMOS Integrated Tactile Sensor with Digital Signal Processing for Robot Application

2012 ◽  
Vol 1427 ◽  
Author(s):  
M. Makihata ◽  
M. Muroyama ◽  
S. Tanaka ◽  
H. Yamada ◽  
T. Nakayama ◽  
...  
Keyword(s):  
Signal Processing ◽  
Digital Signal ◽  
Tactile Sensor ◽  
Force Sensor ◽  
Digital Data ◽  
Wafer Level ◽  
Tactile Sensors ◽  
Low Profile ◽  
Chip Size ◽  
Tactile Receptor

ABSTRACTAn ultra-small tactile sensor with functions of signal processing and digital communication has been prototyped based on MEMS-CMOS integration technology. The designed analog-digital mixed signal ASIC allows many tactile sensors to connect each other on a common bus line, which drastically reduces the number of wire. The ASIC capacitively detects the deformation of a force sensor and sends digital data to the common bus line when the force exceeds a threshold. The digital data contain a physical ID of each sensor, 32-bit sensing data and 16-bit cyclic redundancy check (CRC) code. In this study, a novel wafer-level integration and packaging technology were developed, and a chip-size-packaged tactile sensor with a small footprint (2.5mm×2.5mm) and a low profile (0.27mm) was prototyped and tested. The sensor autonomously sends digital data like a tactile receptor of human.

scholarly journals Analog Signal and Digital Signal Processing in Telecommunication System

2021 ◽  
Vol 1 (6) ◽  
pp. 1-5
Author(s):  
Phong Hung ◽  
Vu Duc Vuong
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Analog Signal ◽  
Digital Data ◽  
Telecommunication System

The term digital signal is a term from a technology that converts an analog signal into digital data so that the signal can be processed more easily and quickly. The term digital itself is a system that only recognizes two conditions. The two conditions are usually represented by the numbers zero and one, on and off, or others. The smallest unit of digital signal is the bit.

scholarly journals Design and Fabrication Technology of Low Profile Tactile Sensor with Digital Interface for Whole Body Robot Skin

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2374 ◽  
Author(s):  
Mitsutoshi Makihata ◽  
Masanori Muroyama ◽  
Shuji Tanaka ◽  
Takahiro Nakayama ◽  
Yutaka Nonomura ◽  
...  
Keyword(s):  
Wafer Bonding ◽  
Integrated Circuit ◽  
Tactile Sensor ◽  
Force Sensor ◽  
Whole Body ◽  
Capacitance Measurement ◽  
Device Structure ◽  
Local Pressure ◽  
Novel Device ◽  
Low Profile

Covering a whole surface of a robot with tiny sensors which can measure local pressure and transmit the data through a network is an ideal solution to give an artificial skin to robots to improve a capability of action and safety. The crucial technological barrier is to package force sensor and communication function in a small volume. In this paper, we propose the novel device structure based on a wafer bonding technology to integrate and package capacitive force sensor using silicon diaphragm and an integrated circuit separately manufactured. Unique fabrication processes are developed, such as the feed-through forming using a dicing process, a planarization of the Benzocyclobutene (BCB) polymer filled in the feed-through and a wafer bonding to stack silicon diaphragm onto ASIC (application specific integrated circuit) wafer. The ASIC used in this paper has a capacitance measurement circuit and a digital communication interface mimicking a tactile receptor of a human. We successfully integrated the force sensor and the ASIC into a 2.5 × 2.5 × 0.3 mm die and confirmed autonomously transmitted packets which contain digital sensing data with the linear force sensitivity of 57,640 Hz/N and 10 mN of data fluctuation. A small stray capacitance of 1.33 pF is achieved by use of 10 μm thick BCB isolation layer and this minimum package structure.

Discrete signals: sampling, quantization and coding

2019 ◽  
pp. 265-298
Author(s):  
Max A. Little
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Digital Signal Processing ◽  
Real World ◽  
Digital Signal ◽  
Digital Data ◽  
Real Numbers ◽  
Representation Problem ◽  
Digital Storage ◽  
Discrete Signals

Digital signal processing and machine learning require digital data which can be processed by algorithms on computer. However, most of the real-world signals that we observe are real numbers, occurring at real time values. This means that it is impossible in practice to store these signals on a computer and we must find some approximate signal representation which is amenable to finite, digital storage. This chapter describes the main methods which are used in practice to solve this representation problem.

Signal processing via sampled-data control theory

Impact ◽  
2020 ◽  
Vol 2020 (2) ◽  
pp. 6-8
Author(s):  
Yutaka Yamamoto ◽  
Kaoru Yamamoto ◽  
Masaaki Nagahara ◽  
Pramod P Khargonekar
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Music Videos ◽  
The Other ◽  
Digital Data ◽  
Sampled Data ◽  
Digital Signals ◽  
Data Control ◽  
Analogue Signals

Digital sounds and images are used everywhere today, and they are all generated originally by analogue signals. On the other hand, in digital signal processing, the storage or transmission of digital data, such as music, videos or image files, necessitates converting such analogue signals into digital signals via sampling. When these data are sampled, the values from the discrete, sampled points are kept while the information between the sampled points is lost. Various techniques have been developed over the years to recover this lost data, but the results remain incomplete. Professor Yutaka Yamamoto's research is focused on improving how we can recover or reconstruct the original analogue data.

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