- 标题
- 摘要
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- 实验方案
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Sensor Fusion for Distance Estimation Under Disturbance with Reflective Optical Sensors using Multi Layer Perceptron (MLP)
摘要： There are many methods to perform distance measurement, among them the reflexive optical sensors, which are low cost but present some issues such as nonlinear response, limited operating ranges and the measurement shows sensitivity to infrared or visible radiation. For this reason, this work presents a sensory fusion model combining three reflective optical distance sensors of different ranges, a color sensor (VIS), an ultraviolet radiation sensor (UV) and an Near infrared sensor (NIR) to estimate the distance using a Multi Layer Perceptron (MLP). The purpose of combining different distance sensors is to have a higher overall range and achieve redundancy in some regions, and the objective of the UV-VIS-NIR sensors is to compensate for the radiation at which the distance sensors are exposed to adjust the measurement. With the attained information, the influence of each type of radiation on the distance measurement was evaluated. It is important to estimate the distance in these ranges because in robotics and automation industries, different associated applications are handled. The MLP was trained switching its architecture between four and sixteen neurons per layer, and between three and five hidden layers. Finally the training and selection of several MLP architectures for sensory fusion with an error lower than 1% was presented.
关键词： Sensor fusion,Distance estimation,Reflective optical sensor,Infrarred sensor,Multi Layer Perceptron (MLP)
更新于2025-09-16 10:30:52
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[IEEE 2018 IEEE International Conference on RFID Technology & Application (RFID-TA) - Macau, Macao (2018.9.26-2018.9.28)] 2018 IEEE International Conference on RFID Technology & Application (RFID-TA) - New Empirical Indoor Path Loss Model using Active UHF-RFID Tags for Localization Purposes
摘要： Indoor is one of the most complicated propagation environments depending on the specific type of buildings structure. In this paper, we present a combination of 2 models using active UHF-RFID tags at 433 MHz: The Dual One Slope Model (DOSM) and the Dual One Slope with Second Order Polynomial Model (DOSSOM). Further, a comparison with different propagation models have been proposed. Our work aims to study, analyze and improve the accuracy of the two new path loss models. Distance errors are determined based on all different propagation models. According to experimental validations, the mean distance error had a value 56 cm using the DOSM, whereas, it had a value of 51 cm using the DOSSOM. In short, distance errors derived from the two new empirical path loss models (DOSM and DOSSOM) closely match real measurements. Thus, referring to the mean distance errors already reached, the stability of our new indoor propagation models will be affirmed.
关键词： Distance estimation,UHF-RFID,Second Order Polynomial Model (SOPM),One Slope Model (OSM),Indoor Localization,Received Signal Strength Indicator (RSSI)
更新于2025-09-09 09:28:46
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[IEEE 2018 Global Smart Industry Conference (GloSIC) - Chelyabinsk, Russia (2018.11.13-2018.11.15)] 2018 Global Smart Industry Conference (GloSIC) - Diagnostics of External Defects of Railway Infrastructure by Analysis of its Images
摘要： An important component of the safe movement of the railway transport is the absence of visible rail defects. The external defects of the track infrastructure were analyzed according to the criteria of detection accuracy and the conditions of applicability of the methods of their detection. For the diagnostics of the railway track, a passive defectoscopy method, based on stereo vision and blur analysis, is proposed. This system can be implemented in a hardware-software control system and is located on ground transport-technological devices.
关键词： railway track,kinematic characteristics,stereo vision,image blur,distance estimation,control system,depth of field,video monitoring
更新于2025-09-04 15:30:14