제어로봇시스템학회:학술대회논문집
- 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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- Pages.187-192
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- 1992
Position estimation using combined vision and acceleration measurement
초록
There are several potential error sources that can affect the estimation of the position of an object using combined vision and acceleration measurements. Two of the major sources, accelerometer dynamics and random noise in both sensor outputs, are considered. Using a second-order model, the errors introduced by the accelerometer dynamics are reduced by the smaller value of damping ratio and larger value of natural frequency. A Kalman filter approach was developed to minimize the influence of random errors on the position estimate. Experimental results for the end-point movement of a flexible beam confirmed the efficacy of the Kalman filter algorithm.
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