Towards Improved Inertial Navigation by Reducing Errors Using Deep Learning Methodology

Round 1

Reviewer 1 Report

Line 57-64: There are some papers that show counter statement to "bias scale factor drift are stochastic." e.g. this paper. One argument is that bias scale factor drift seem to be stochastic due to the lack of observability to disturbance. So, please rephrase line 57-64 to be less assertive.

Line 194- 197 & 253- 259: The notion of "step size" is not very clear to the reader. Is a "step size" of 10, duplication nine times of one sample data collected from the IMU or its ten sample data collected continuously?

Table 8 and Table 9: Instead of presenting the percent error in Table 8 and Table 9. Please draw a 2D graph showing the tracks and error during different test runs.

To understand the validity of the experimental data. The following information are important and should be included!

1. What is the rate random walk and acceleration random walk of both IMUs? 

2. What is the environmental conditions for training the CNN model and toy RC & train experiments?

3. How long does it take for conducting the toy RC & train experiments? 

4. Any calibration steps for IMU before, during the toy RC & train experiments? 

 

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

This contribution presents original ideas in the study and advances the previous research in this area. The level of the originality of contribution to the existing knowledge with an emphasis on the paper’s innovativeness in both theory development and methodology used in the study is very high.
This work makes a significant practical contribution and it makes impact on the research work on the research community. The quality of arguments, the critical analysis of concepts, theories and findings, and consistency and coherency of debate are well addressed in this paper. The paper has a good writing style in term of accuracy, clarity,
readability, organization, and formatting.

-Please introduce a flow chart of the control strategy in order to have an overview of the proposed technique.

The paper is really very good and deserves publication!!

 

Concerning the cited literature you can consider the following papers to improve the tutorial aspects of the paper.

Lindner, L. et al. Machine vision system for UAV navigation (2017) 2016 International Conference on Electrical Systems for Aircraft,
Railway, Ship Propulsion and Road Vehicles and International Transportation Electrification Conference, ESARS-ITEC 2016 Ivanov, M. et al. Influence of data clouds fusion from 3D real-Time vision system on
robotic group dead reckoning in unknown terrain (2020)
IEEE/CAA Journal of Automatica Sinica, 7 (2), art. no. 9016393, pp. 368-385. Lindner, L. et al. Machine vision system errors for unmanned aerial
vehicle navigation (2017) IEEE International Symposium on Industrial
Electronics, art. no. 8001488, pp. 1615-1620.

Author Response

Please see the attachment.

Author Response File: Author Response.docx