Dead reckoning navigation of a mobile robot using an indirect Kalman filter

Park, KyuCheol; Chung, Dohyoung; Chung, Haseung; Lee, Jang Gyu

doi:10.1109/mfi.1996.572169

Cited by 15 publications

(3 citation statements)

References 8 publications

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“…used a fusion technique which Extended Kalman Filter for predict the occupancy of grid map in mobile robot pose tracking [5]. Other researchers implement dead reckoning via indirect kalman filter to navigate autonomous mobile robot [6]. KyuCheol Park et.al.…”

Section: Introductionmentioning

confidence: 99%

“…KyuCheol Park et.al. described that the autonomous mobile gives a precise position and angle direction and the autonomous mobile is using encoder and gyroscope as the sensor and Kalman filter had been implemented in the autonomous mobile [6].…”

Section: Introductionmentioning

confidence: 99%

“…use Kalman filter in localize the position of the mobile robot using encoder that attach on the mobile robot wheel [6]. Also their used gyro for measuring the position direction of the mobile robot [7].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Height Measurement using Sonar Sensor Based on Single Dimension Kalman Filter in Embedded Controller

Misnan

Arshad

Shauri

et al. 2012

2012 IEEE International Conference on Control System, Computing and Engineering

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The aim of this paper is to evaluate real-time accurateness of low-altitude height measurement using a single sonar sensor via Kalman filter algorithm in embedded controller. The function of the one dimension embedded Kalman filter of sonar sensor is to reduce and resolve the error of low altitude height measurement that produced from the sensor for mapping application. Series data of varied height measurement with Kalman filter was gathered and implemented using a 16-bit microcontroller unit. A structure model was constructed to allow for dynamic height measurement between ground surface and the sensor.The tabulated data are shown for comparison of accuracy and error analysis between both with Kalman and without Kalman filter. After several scanned surfaces and analysis of the recorded data, the technique shows the usefulness in height measurement application that used surface scan method which the sonar project to the ground such as UAV in order to reduce error of the detected varied height.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%