Indoor Map Boundary Correction Based on Normalized Total Least Squares of Condition Equation
Publication: Journal of Surveying Engineering
Volume 147, Issue 4
Abstract
Indoor high-precision maps are necessary for many applications, including robot navigation and location-based services. Raw indoor map boundaries are too irregular and coarse to be used in practical applications directly; thus, correction for indoor map boundaries is necessarily carried out. Considering that least-square (LS) methods cannot process the errors in a coefficient matrix, we proposed a normalized total least-squares of condition (NTLSC) equation method to solve for polylines. The proposed NTLSC is more robust than LS with respect to the ill-posed problem in iteration, and linearization need not be employed, which simplifies the complexity of the formula. Aiming at the curves in the map, an iterative LS (ILS) strategy was designed to rectify it for high precision. However, due to the use of different correction models, there will be some tiny gaps between the curve and polylines. Therefore, a junction processing method was put forward, which is an indispensable step to preserve the integrality of the indoor map boundary. Finally, the indoor map boundaries of two scenes were refined by the proposed method, and the results of two perspectives of qualitative and quantitative evaluations indicate that the proposed method can effectively correct irregular and coarse map boundaries.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request, including original data of Scenes 1 and 2, corresponding coordinates of broken points extracted from the original data, and application source code (MATLAB code).
Acknowledgments
We would like to express our appreciation to Mr. Shoujun Jia for the help in data collection of Scene 1. This work is supported by the National Major Science and Technology Projects of China (Nos. 2016YFB0502104 and 2018YFB1305000), the National Natural Science Foundation of China (No. 41671451), the Fundamental Research Funds for the Central Universities of China (No. 22120190195), and Shanghai Municipal Natural Science Foundation (No. 19ZR1459700).
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Received: Sep 22, 2020
Accepted: Mar 22, 2021
Published online: Jun 18, 2021
Published in print: Nov 1, 2021
Discussion open until: Nov 18, 2021
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