# Kinematic In Situ Self-Calibration of a Backpack-Based Multi-Beam LiDAR System
## 6 Conclusions  
This study investigated kinematic in situ self-calibration to frequently re-calibrate the backpack-based MBL system using on-site data for handling unstable measurements of the sensor. In order to determine the minimum network configuration for kinematic self-calibration, simulation experiments were conducted beforehand. First, a full network of the simulated datasets was generated, and self-calibrations were performed by reducing the number of scans, the size of the test site, the number of incorporated planes, and the number of points. The accuracies of the experiments were analyzed by examining the RMSE of the estimated APs to determine the minimum network configuration. The results of the simulation experiments show relatively stable performance with a minimum network configuration of at least two scans, three planes that are orthogonal to each other, and around two thousand points used. Based on this preliminary analysis, kinematic self-calibration using real datasets was then performed. The datasets were acquired while the user was wearing a backpack system and walking along a corridor. The accuracy of kinematic self-calibration was evaluated by investigating the planar misclosure, measurement residuals, correlation coefficients, and estimated parameters and their standard deviations. The results demonstrate that the kinematic self-calibration of the backpack-based MBL system could improve the point cloud accuracy with the RMSE of planar misclosure up to 81%. Moreover, the effectiveness of the proposed approach in terms of time and cost was also addressed.  
After the various experiments and analysis using the proposed kinematic in situ self-calibration of the backpack-based MBL system, the contributions of this study can be summarized as follows. First, self-calibration of MBL was analyzed with respect to various network configurations. The minimum network configuration for the kinematic in situ self-calibration of the backpack-based MBL system and its performance were found through various experiments. Secondly, the kinematic in situ self-calibration of the backpack-based MBL system can perform using on-site datasets, reaching the higher accuracy of point cloud. In addition, this research can serve as a guideline for users who require the self-calibration of a backpack-based MBL system to improve overall accuracy and to generate point cloud data for precise mapping or surveying. Future studies will mostly focus on: (1) the development of real-time automatic plane matching for automatic in situ calibration; (2) outlier removal during the iteration of least squares based on statistical analysis to maximize calibration accuracy.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Approaches**} & \multicolumn{2}{c}{**RMSE of Planar Misclosure**} & \multirow{2}{*}{**Improvement**} & \multirow{2}{*}{**Sensor**} \\ \cline{2-2} \cline{4-4}  & **Static** & & **Kinematic** \\ \hline [PERSON] and [PERSON] [25] & 0.013 m & & 63.8\% & HDL-64E \\ [PERSON] and [PERSON] [28] & 0.013 m & & 40\% & HDL-64E \\ [PERSON] [29] & & 0.023 m & 37.8\% & HDL-64E \\ [PERSON] and [PERSON] [30] & 0.008 m & 0.014 m & 41–71\% & HDL-32E \\ [PERSON] et al. [31] & 0.025 m & & 20\% & VLP-16 \\ Proposed & & 0.007 m & 35–81\% & VLP-16 \\ \hline \hline \end{tabular}
\end{table}
Table 17: Comparison with other self-calibration results.  
**Author Contributions:** H.S.K. was responsible for developing the methodology and writing the original manuscript, C.K. provided the backpack system, Y.K. helped revise the manuscript, and K.H.C. supervised the research. All authors have read and agreed to the published version of the manuscript.  
This work was supported by a National Research Foundation of Korea (NRF) grant (no. 2019R1A2C1011014) funded by the Korean government (MSIT).  
Data Availability Statement: Data sharing not applicable.  
The authors are grateful to C2L Equipment (www.c2l-equipment.com) for helping to develop the backpack system for this research.  
The authors declare no conflict of interest.