Muli-sensor Calibration Optimization Method of Mobile Robot Based on Stationary and Moving Object Observation ConsistencyConstraint

doi:10.3969/j.issn.1000-1093.2017.08.022

Abstract

Abstract: A calibration optimization method of camera and laser rangefinder based on stationary and moving object observation consistency constraint is proposed to address the problem of spatial observation consistency from heterogeneous multi-sensor in the process of mobile robot navigation in unknown environment. A covariance intersection method is used to fuse the bearing state of moving object on image plane, and Kalman and probabilistic data association filters are used to resolve the bearing state fusion of corner feature in the situations of “one-to-one” and “one-to-many”. On this basis, the objective function is generated using the bearing errors before and after fusion of image projections of stationary and moving objects, and the calibration parameters of camera and laser rangefinder are optimized using nonlinear optimization method. Experimental results show that the proposed method can be used to improve the observation consistency of multi-sensor, and the effectiveness of the mentioned methods is verified. Key

Key words: controlscienceandtechnology, SLAM, objecttracking, multi-sensorcalibration, multi-sensorinformationfusion

CLC Number:

TP249

WU Ming, ZHANG Guo-liang, LI Lin-lin, FU Guang-yuan, LI Cheng-jian. Muli-sensor Calibration Optimization Method of Mobile Robot Based on Stationary and Moving Object Observation ConsistencyConstraint[J]. Acta Armamentarii, 2017, 38(8): 1630-1641.

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第38卷
第8期2017 年8月兵工学报ACTA
ARMAMENTARIIVol.38No.8Aug.2017

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