ZigBee phase shift measurement approach to mobile inspection robot indoor positioning techniques

Śmieja, Michał

doi:10.29354/diag/94498

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…The ZigBee terminal node part includes basic functional modules such as power supply part, pressure and motion sensor part, radio frequency circuit, etc. ZigBee coordination: The device contains interfaces such as radio frequency circuits, serial ports, LEDs, buttons, and other peripheral circuits [ 16 ]. The part on the PC side contains the PC and is a combination of the gateway part.…”

Section: Model Predictive Control and Sensor Network Model Designmentioning

confidence: 99%

Feedback Delay of Sports Intelligent Learning System Based on Model Predictive Control

2022

Computational Intelligence and Neuroscience

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In this paper, a trajectory tracking controller based on linear time-varying model prediction is developed, and the model predictive control theory based on the six degrees of freedom dynamic model and tire model is applied. Combined with the soft constraint of turning angle and the control algorithm to ensure the stability, the trajectory tracking is realized. The terminal node is a wearable device. The terminal node is equipped with a pressure sensor and attitude sensor network to collect human data, and then the terminal node sends the data to the ZigBee network. The data in the sensor network will be received by the gateway, and the data will be processed and displayed on the PC software after being received by the gateway. Finally, the data is saved to the remote server for archiving. The application of intelligent learning systems in sports makes up for many shortcomings of traditional sports. The teaching of the course consists of seven types of intelligent courses, which not only conform to the spirit of high-quality education but also combine the shortcomings of traditional physical education learning and combines several intelligent theories and the need for time development. The purpose is to develop a new sports model suitable for students’ all-round development. Under the guidance of the theory of intelligent learning system, this paper establishes a new and diverse movement model, including various educational models, educational contents, educational methods, student-based learning model, and multidimensional evaluation. By comparing and analyzing the results of the two groups, the multiple intelligences physical education is more suitable for the development of modern students’ various intelligences. According to the physical education learning questionnaire, students also learn more methods and contents and accept diversified teaching evaluation, which expands the development direction of students.

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Section: Model Predictive Control and Sensor Network Model Designmentioning

confidence: 99%

Feedback Delay of Sports Intelligent Learning System Based on Model Predictive Control

2022

Computational Intelligence and Neuroscience

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Intelligent Light Control System Based on Zigbee

Wang

2022

Computational Intelligence and Neuroscience

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This system uses Freescale i.MX283 chip as the main control core of the control panel and LPC824 as the main control core of the light control point. ZigBee communication local area network is built. The ZigBee network is used to search all the nodes and display them on the control interface stably. The controller can selectively control the node and communicate with ZigBee. It supports simple and convenient human-computer interaction interface. The control panel can control RGB lamps of lamp control nodes as follows: control the light on and off, adjust the brightness of the light, toggle the color of the light, control the gradient of the light, control the flashing of RGB lamp, control timing switch of RGB lamp, realize the scene effect of the light, etc. After testing, the system is stable and applied to many lighting control occasions.

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Research on the Positioning and Recognition of an Intelligent Inspection Robot in Substations

Xing

2023

IJAT

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The substation inspection robot follows the set path when working autonomously, and accurate positioning of the robot while moving is required to ensure that the route does not deviate. This study briefly introduces a substation inspection robot, an odometer-based positioning algorithm, radio frequency identification (RFID), and a machine vision-based positioning algorithm, and improves the former algorithm by RFID. Subsequently, the three positioning algorithms were compared. The results showed that the RFID+machine vision-based positioning algorithm exhibited the highest accuracy among the three algorithms tested under the same cycle number, and its positioning error remained stable as the cycle number increased.

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ZigBee phase shift measurement approach to mobile inspection robot indoor positioning techniques

Cited by 3 publications

References 24 publications

Feedback Delay of Sports Intelligent Learning System Based on Model Predictive Control

Feedback Delay of Sports Intelligent Learning System Based on Model Predictive Control

Intelligent Light Control System Based on Zigbee

Research on the Positioning and Recognition of an Intelligent Inspection Robot in Substations

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