DocumentCode :
2669135
Title :
Development an intelligent power detection system for mobile robots
Author :
Kuo, L.S. ; Yungchin, Lin ; Sheng, Victor S. ; Jheng, S.J.
Author_Institution :
Dept. of Electr. Eng., Nat. Yunlin Univ. of Sci. & Technol., Douliou
fYear :
2008
fDate :
16-18 July 2008
Firstpage :
637
Lastpage :
641
Abstract :
The paper presents an intelligent power detection system for a mobile robot. We use four current sensors to measure the current variety of the mobile robot, and use multilevel multisensor fusion method to detect current sensor and voltage signals status. Moreover, a two level method is used to isolate faulty measured value such that more exact current and voltage status to be obtained. In this method, a redundant management method and a statistical prediction method are used in levels one and two, respectively. We design the power detection and isolation module using HOLTEK microchip according to the redundant management method. This module can transmit measured value and estimated statue to main controller (IPC) using series interface (RS232). However, it is possible that this method is faulty. In this case, the IPC can decide an exact power measured value and faulty status according the statistical signal prediction method. Then we can predict the residual power of mobile robots using polynomial regression algorithm. Finally, we implement the proposed method on the experiment scenario of can set a power threshold value to calculate the critical time for the mobile robot. Meanwhile, experimental results are given to show the feasibility of the proposed method.
Keywords :
mobile robots; power system control; power system management; prediction theory; regression analysis; sensor fusion; HOLTEK microchip; IPC; RS232; current sensors; intelligent power detection system; mobile robots; multilevel multisensor fusion; polynomial regression algorithm; power isolation; redundant management method; statistical prediction method; statistical signal prediction method; Current measurement; Energy management; Intelligent robots; Intelligent sensors; Intelligent systems; Mobile robots; Power measurement; Prediction methods; Sensor fusion; Voltage; Intelligent power detection system; Mobile robot; Polynomial regression algorithm; Redundant management method; Statistical signal prediction method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
Type :
conf
DOI :
10.1109/CHICC.2008.4605684
Filename :
4605684
Link To Document :
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