scholarly journals Robot Face and Its Integration to the Mobile Robot for Wireless Signal Collection in the Fingerprinting-Based Indoor Positioning System

2021 ◽  
Vol 2107 (1) ◽  
pp. 012023
Author(s):  
M A H Sarhan ◽  
A H Ismail ◽  
M N Ayob ◽  
M S Mohd Hashim ◽  
M S M Azmi ◽  
...  
Keyword(s):  
Data Collection ◽  
Indoor Positioning ◽  
Service Robot ◽  
Positioning System ◽  
Wireless Data ◽  
Daily Lives ◽  
Signal Collection ◽  
Wireless Signal ◽  
Wireless Data Collection ◽  
Indoor Positioning System

Abstract The wireless data collection for instance the Received Signal Strength (RSS) of the Wireless Fidelity (Wi-Fi) remained unfavourable in the Indoor Positioning System utilizing the signal fingerprinting approach. This is because the enormous sampling time and routines works making it tedious human labour. To alleviate this issue, we propose to use a robot for wireless data collection. The robot, named ‘ICSiBOT’ is a service robot with multiple purpose such as assisting human in daily lives, guest or hospitality robot and man others. This paper mainly describes the ICSiBOT robot face with speech recognition technology and the integration of the robot face to the motion controller. The experimental was conducted to see the correlation between the synthesized instructions from the speech in terms of distance need to be travelled i.e., the location for wireless signal collection and translate them into actual distance travelled. The results showed that the robot is able to travel to the specific distance as instructed to the robot face.

scholarly journals Employing DIALux to relieve machine learning training data collection when designing indoor positioning system

2021 ◽  
Author(s):  
Shao-Hua Song ◽  
Dong Chang Lin ◽  
Yang LIU ◽  
Chi-Wai Chow ◽  
Yun-Han chang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Indoor Positioning ◽  
Training Data ◽  
Positioning System ◽  
Indoor Positioning System

scholarly journals High-Precision RTT-Based Indoor Positioning System Using RCDN and RPN

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3701
Author(s):  
Ju-Hyeon Seong ◽  
Soo-Hwan Lee ◽  
Won-Yeol Kim ◽  
Dong-Hoan Seo
Keyword(s):  
High Precision ◽  
Distance Estimation ◽  
Sampling Period ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Positioning System ◽  
Positioning Systems ◽  
Positioning Errors ◽  
Location Determination ◽  
Indoor Positioning System

Wi-Fi round-trip timing (RTT) was applied to indoor positioning systems based on distance estimation. RTT has a higher reception instability than the received signal strength indicator (RSSI)-based fingerprint in non-line-of-sight (NLOS) environments with many obstacles, resulting in large positioning errors due to multipath fading. To solve these problems, in this paper, we propose high-precision RTT-based indoor positioning system using an RTT compensation distance network (RCDN) and a region proposal network (RPN). The proposed method consists of a CNN-based RCDN for improving the prediction accuracy and learning rate of the received distances and a recurrent neural network-based RPN for real-time positioning, implemented in an end-to-end manner. The proposed RCDN collects and corrects a stable and reliable distance prediction value from each RTT transmitter by applying a scanning step to increase the reception rate of the TOF-based RTT with unstable reception. In addition, the user location is derived using the fingerprint-based location determination method through the RPN in which division processing is applied to the distances of the RTT corrected in the RCDN using the characteristics of the fast-sampling period.

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