A method for improving the pose accuracy of a robot manipulator based on multi-sensor combined measurement and data fusion

An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time...

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Bibliographic Details
Published inSensors (Basel, Switzerland) Vol. 15; no. 4; pp. 7933 - 7952
Main Authors Liu, Bailing, Zhang, Fumin, Qu, Xinghua
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 02.04.2015
MDPI
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Summary:An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%~78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 x 0.8 x 1 ~ 2 x 0.8 x 1 m in the field of view (FOV) is indicated by the experimental results.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s150407933