Study On Precision Method Integrated Laser And INS For Indoor Close-range Posintioning

The positioning of MAVs under indoor environment is the premise of effective work. Theincreased application for MAVs in military reconnaissance, anti-riot counter-terrorism, securitymonitoring, disaster relief and other areas, requires higher accuracy of positioning. This paper selecteda2D laser range finder as external sensor to assist a MIMU for precision indoor positioning of MAVs.This paper explained the meaning and objectives of the laser scan matching problem，theoretically. We analysis the principle and characteristic of several typical laser scan matchingalgorithms, and give some improvement strategies to reduce error correspondences or improve thecompute rate. We designed residue points based algorithms, the corner matching algorithm and ICPalgorithm. Then we presented a mix strategy named RIC, which combines four algorithms. The mixstrategy chose different matching algorithms by determining whether scans contain enough linesegments. Residue points based algorithm or rotation search/least squares algorithm was used toprovide an initial estimate for the subsequent calculation. Simulations and experiments showed thatthis combined algorithm can work in various surroundings, and satisfy the requirement of accuracy..This paper builded a indoor coordinate system witch was similar to the geographic coordinatesystem as navigation coordinate system. We simplified differential funcations and error models ofnavigation parameters. Then we give error models of the MIMU system, by analysing error sourcesand mechanisms. At the same time, we discussed error sources of micro inertial components and laserscan matching, and modeled random errors.Kalman filter was designed to integrate the position and orientation provided by laser scanmatching and MIMU system, respectively. We estimated errors of the MIMU system and the laserscan matching. Feedback corrections and output corrections were used in the MIMU system or laserscan matching respectively, inoder to improve the positioning accuracy, Simulations and experimentalresults showed that the integrated positioning method based on R-I-C mix algorithm and Kalman filtercan achieve precision positioning under indoor environments.