Development of Autonomous Mobile Robot with 3DLidar Self-Localization Function Using Layout Map
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsReview grammar, some few errors.
Reduce considerably the length of the paper, focus on the contribution.
Add a "control diagram" showing the main signals, including trajectory generation, the control loop with the actuation, measured and error signals.
1. What is the main question addressed by the research?
The main contribution is the matching of previous information of wall surface layout, with point cloud from onboard sensors (3D Lidar), despite some small differences between previous information and current situation (location of walls and obstacles), and fusing them through a Particle filter to obtain robot´s position. Also, the utilization of a shortest rout algorithm for route determination (trajectory) between fixed waypoints, and path following, as well as obstacle avoidance by modifying on route the trajectory. 2. What parts do you consider original or relevant for the field? Whatspecific gap in the field does the paper address? The mentioned contribution. This is, the integration of recorded data (photos or map layouts) with updated 3D point cloud measured data (and odometry) to infer through a stochastic filter the position of the vehicle, and the use of optimal trajectory generation, path following, and obstacle avoidance by locally generation of new waypoints.
3. What does it add to the subject area compared with other published
material? The useful integration of the techniques, and the actual experimental tests using real data from aerial photos and an autonomous differential-wheeled cart.
4. What specific improvements should the authors consider regarding the
methodology? What further controls should be considered? Reduce the length of the article, leaving what is relevant (it looks as if a thesis was employed to write it - uses the word "Chapter" in some parts). In terms of controls, be more explicit, including an overall bloc diagram (controller, plant, trajectory generation, etc.) where signals are detailed.
5. Please describe how the conclusions are or are not consistent with the
evidence and arguments presented. Please also indicate if all main questions
posed were addressed and by which specific experiments. Conclusion is consistent, as it details what was described in more detail throughout the paper. All main questions were addressed by the experiment carried out, although not much detail is given for the experiment (this can be improved after reducing the length of the paper by taking out unnecessary parts).
6. Are the references appropriate? Can be improved.
7. Please include any additional comments on the tables and figures and
quality of the data. Captions and labeling have errors. Label fonts sizes are too small, Figure 50 and 421, and two more similar figures below (pages 39 and 40). Figures with portions of maps, layouts, cloud points, etc., include geographical orientation, and length scales. Figure 20 is not clear.
Comments on the Quality of English Language
Good in general
Author Response
Authors Responses to comments made by reviewers
The authors do acknowledge and appreciate the reviewers’ comments. The responses to the reviewers’ concern and comments have been prepared as detailed by the following table report. Additionally, the revised manuscript has been edited on the basis of the report and relevant edited sections are highlighted in yellow.
Reviewers’ comments |
Authors Responses to comments made by the Reviewers |
Revised sections in the original paper |
Reviewer 1: Comments |
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1. Review grammar, some few errors. |
To address this concern, the authors checked grammar, spellings and punctuations. |
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2. Reduce considerably the length of the paper, focus on the contribution. |
We have reduced the paper from 41 pages to 23 as advised |
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3. Add a "control diagram" showing the main signals, including trajectory generation, the control loop with the actuation, measured and error signals. |
Control loop: Looped between Navigation and trolley drive unit. ・Measurement signal: 3D point cloud from Velodyne and rotation angle from the encoder. ・Other data between processing has been described. |
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Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for Authors1. The caption of some figures are lost, such as Figure 3. The numbering of the figures is also chaotic.
2. The structure of the paper should be improved. It is best to describe in order of method, equipment, and results.
3. The efficiency of mapping should be reported.
4. The technical details of the method should be supplemented, such as Ndt matching and path following algorithm.
5. The system configuration shown in Figure 1 includes multiple modules, but lacks subsequent evaluation.
6. The figure 28 of building length comparison is confusing. It is unclear how to achieve the comparative effect.
7. No comparison is performed to prove the superiority of the proposed method.
8. The comprehensive related work should be added, including Knowledge-based engineering approach for defining robotic manufacturing system architectures, New time-differenced carrier phase approach to GNSS/INS integration, A Novel Airspace Planning Algorithm for Cooperative Target Localization, MR-DCAE: Manifold regularization-based deep convolutional autoencoder for unauthorized broadcasting identification, Fine-grained modulation classification using multi-scale radio transformer with dual-channel representation.
Comments on the Quality of English LanguageMinor editing of English language required.
Author Response
Authors Responses to comments made by reviewers
The authors do acknowledge and appreciate the reviewers’ comments. The responses to the reviewers’ concern and comments have been prepared as detailed by the following table report. Additionally, the revised manuscript has been edited on the basis of the report and relevant edited sections are highlighted in yellow.
Reviewers’ comments |
Authors Responses to comments made by the Reviewers |
Revised sections in the original paper |
Reviewer 2: Comments |
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1. The caption of some figures are lost, such as Figure 3. The numbering of the figures is also chaotic. |
We have refined the captioning of the figure to improve legibility |
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2. The structure of the paper should be improved. It is best to describe in order of method, equipment, and results. |
We have refined the structure to the proposed. The methods section turned out to be long so we split this in to two, however we can combine them if need arise |
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3. The efficiency of mapping should be reported. |
We have refined the reporting of the results |
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4. The technical details of the method should be supplemented, such as Ndt matching and path following algorithm. |
The NDT matching and path following algorithm details have been supplemented |
Section 4.0 and section 3.3.4 |
5. The system configuration shown in Figure 1 includes multiple modules, but lacks subsequent evaluation. |
We have addressed this in the current draft and addressed each of the module as a unit |
Section 2.0/ section 3.0 |
6. The figure 28 of building length comparison is confusing. It is unclear how to achieve the comparative effect. |
We have refined the results to include clear description as well as figures that best captures the matter |
Section 4.o on evaluation |
7. No comparison is performed to prove the superiority of the proposed method. |
There was no significant difference compared to the estimated position of existing 3D self-location estimation (NDT Matching), and other studies, thus suggesting at par performance on studies that report map creation. Further details of estimated localization have been provided comparing against literature review results in the current draft Ideally, there is a challenge with comparison of map generating studies, since the objective is autonomous movement and map generation in realtime. |
Section 4.1 and 4.2 |
8. The comprehensive related work should be added, including Knowledge-based engineering approach for defining robotic manufacturing system architectures, New time-differenced carrier phase approach to GNSS/INS integration, A Novel Airspace Planning Algorithm for Cooperative Target Localization, MR-DCAE: Manifold regularization-based deep convolutional autoencoder for unauthorized broadcasting identification, Fine-grained modulation classification using multi-scale radio transformer with dual-channel representation. |
We have limited the discourse to the current state of SLAM and Map generation in the draft. Some of the suggested works have been incorporated in the work as well. |
Section 1.0 |
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe Authors proposed to develop a concept of controlling an autonomous mobile robot with self-localization capability using simultaneous localization and mapping (SLAM). SLAM algorithms are based on computational geometry concepts and computer image analysis methods, often including AI artificial intelligence techniques. They are used more and more often as effective support for the broadly understood navigation of industrial robots. The SLAM concept is based on mapping and the so-called odometry implemented in relation to reality, both virtual and augmented. SLAM enables mobile robots to create maps of their working environment using devices such as lidar, radar and sonar sensors. They enable navigation and tracking of the robot's trajectory without prior knowledge of the structure of the working environment. The authors of the work proposed and created an original robotic system using, among others, 3D SLAM mobile phone, eliminating the need to manually create maps. In order to ensure autonomous movement of the mobile robot, the proposed system also has other desirable functions built-in, such as the ability to create routes, track and detect obstacles, etc. The tests performed showed that the proposed system minimized the number of self-positioning errors and optimized the robot's autonomous movement. Finally, the authors pointed out the effectiveness of the created system, in particular as a support for the automation of processes occurring, e.g. during warehouse work.
The work is methodologically well constructed and contributes to the expansion of the scientific area undertaken by the Electronics journal, in particular to the development of scientific knowledge of a utilitarian nature. However, in order to take into account editorial requirements, the article requires significant corrections, in particular regarding the qualitative form and stylistic and punctuation nature. Belongs:
¾ complete the descriptions of all the quantities used in the rules and formulas used - it is best to place them directly under the formulas,
¾ complete the descriptions under the drawings, e.g. line 133, 283, 685, 695,698, 754, 761, 770, 778,
¾ line 221: syntactic error – missing (.) should be Figure. 9. – correct captions in other drawings,
¾ line 124: syntactic error – missing (.) should be 2.1. – correct in other paragraphs,
¾ line 547, 550: the description should appear above the table,
¾ correct the numbering of drawings, e.g. line 715,
¾ improve and standardize the quality (resolution) of drawings, currently it is insufficient,
¾ the "Conclusions" chapter is too modest in relation to the volume of the work, there is no broader development of comments of a utilitarian nature: e.g. about the perspective of application of the proposed method, etc.,
¾ the “References” chapter seems to be quantitatively modest: in particular, the small share of works published in Electronics… is surprising.
Author Response
Authors Responses to comments made by reviewers
The authors do acknowledge and appreciate the reviewers’ comments. The responses to the reviewers’ concern and comments have been prepared as detailed by the following table report. Additionally, the revised manuscript has been edited on the basis of the report and relevant edited sections are highlighted in yellow.
Reviewers’ comments |
Authors Responses to comments made by the Reviewers |
Revised sections in the original paper |
Reviewer 3: Comments |
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1. complete the descriptions of all the quantities used in the rules and formulas used - it is best to place them directly under the formulas, |
We have updated the draft to refine the legibility and interpretability of equations |
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2. complete the descriptions under the drawings, e.g. line 133, 283, 685, 695,698, 754, 761, 770, 778, |
We have refined the captions for the figures as needed |
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3. line 221: syntactic error – missing (.) should be Figure. 9. – correct captions in other drawings, |
We have refined the captions for the figures as needed |
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4. line 124: syntactic error – missing (.) should be 2.1. – correct in other paragraphs, |
We have refined the section and paragraphs in the current draft |
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5. line 547, 550: the description should appear above the table, |
We have edited the document to capture the suggested advice |
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6. correct the numbering of drawings, e.g. line 715, |
We have edited the document to capture the suggested advice |
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7. improve and standardize the quality (resolution) of drawings, currently it is insufficient, |
We have edited the document to capture the suggested advice |
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8. the "Conclusions" chapter is too modest in relation to the volume of the work, there is no broader development of comments of a utilitarian nature: e.g. about the perspective of application of the proposed method, etc., |
We have updated the work to capture the suggested changes |
Section 5.0 |
9. the “References” chapter seems to be quantitatively modest: in particular, the small share of works published in Electronics… is surprising. |
We have updated the document with the references we could find relating to the current topic from electronics journal. |
Section 1. |
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsAccept.