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Article
Peer-Review Record

A Novel Algorithm for Ship Route Planning Considering Motion Characteristics and ENC Vector Maps

J. Mar. Sci. Eng. 2023, 11(6), 1102; https://doi.org/10.3390/jmse11061102
by Qinghua He 1, Zhenyu Hou 2 and Xiaoxiao Zhu 1,*
Reviewer 1: Anonymous
Reviewer 2:
J. Mar. Sci. Eng. 2023, 11(6), 1102; https://doi.org/10.3390/jmse11061102
Submission received: 2 April 2023 / Revised: 15 May 2023 / Accepted: 18 May 2023 / Published: 23 May 2023
(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors' purpose is to present an algorithm for ship route planning considering motion characteristics and ENC vector maps. The authors argue that they conducted experiments to verify the effectiveness and advantages of the proposed algorithms.

In my opinion, the contribution of the paper is not clear, and the idea does not seem to be novel. The paper lacks analysis and comparative. The authors need to show significant improvement over other approaches on several test scenarios to claim the advancement and novelty of their proposal.

Some points must be taken to improve the quality of the article:

* The paper contains grammatical mistakes and typos. The whole paper must be carefully reviewed.

* In the abstract, the result of this work must be described briefly with data to show the effectiveness and advantages of proposed algorithm. “In the final part, we also conducted experiments to verify the effectiveness and advantages of proposed algorithms.”

* The main contributions should be reviewed and stated in a clear form.

* Should have text between section title and section subtitle (e.g., between 2 and 2.1, and so on).

* Transitions from section to section should be smoother, please work on this issue to enhance readability.

* It is not clear what are the advantages, disadvantages, issues, etc. related to the implementation of the Rapid-exploring Random Tree algorithm in their proposal. The text should guide the reader to understand why the authors selected and implemented this approach into their proposal over other methods.

* In the results, there is not a comparison concerning the state of the art. The results are insufficient to provide a valid evaluation of the proposed method. Moreover, should be performed a deep comparative study with several complex scenarios.

* Furthermore, it should be performed a deep comparative study using statistical tests (statistical significance). It is recommended to employ a parametric or non-parametric statistical test for statistical analysis.

*In Section 4, there is a lack of parameter setting discussion for the simulation settings. The parameter values have not been described. How would the result of your implementation vary with increasing/decreasing those values?

* The conclusion section should be improved to provide real useful conclusions. Not to be an overview of the previous paragraphs.

* On the conclusions, the authors need to provide solid and insightful future research directions in a separate paragraph.

* More references to path planning papers should be reviewed and included, like: “Hybrid path planning algorithm based on membrane pseudo-bacterial potential field for autonomous mobile robots,” “Mobile robot path planning using membrane evolutionary artificial potential field,” and "Mobile robot path planning using a QAPF learning algorithm for known and unknown environments".

* The references must be carefully reviewed, updated, and extended. The number of references is low for a journal paper (usually 40-50 references for journal papers), please consider the previous comments on this issue.

 

* A review of the state of the art is required.

Comments on the Quality of English Language

* The paper contains grammatical mistakes and typos. The whole paper must be carefully reviewed.

Author Response

Please see the file Response to reviewers

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The article presents a new algorithm to plan routes automatically (VK-RRT*), using electronic navigation chart (ENC) vector data and Delaunay triangulation.

In general, the topic is relevant and current, but some basic considerations were not addressed for application in unmanned surface vehicles (USV).

Were the International Regulations for Preventing Collisions at Sea, more commonly known as the COLREGS, considered in the design of the algorithm? Note that this is mandatory for automatic ship navigation systems.

Is it a COLREGS-compliant collision avoidance system?

The authors claim that one of the contributions of the article is the fact that the algorithm considers Ship kinetic constraints, in the simulated experiments this was not addressed, so it is not possible to verify the effectiveness of such a statement.

The weak point of the article is in the presented results, because the comparison with simpler versions of the RRT are not enough, in addition the system was only tested in a simulated environment and without traffic (which usually does not happen).

 

Author Response

Please see the file Response to reviewers

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

In this revised version of the manuscript, the authors have addressed some of my suggestions and comments. However, in my opinion, there are still some comments and suggestions that must be taken into consideration to improve the quality of the article.

* The main contributions should be reviewed and stated in a clear form.

 

* The conclusions must be improved.

Comments on the Quality of English Language

None.

Author Response

Thanks for your approval of our paper. We had corrected the conclusion and minor grammar errors. Thanks again for your help in the improvement of our paper.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors satisfactorily revised the article, so I believe it is in line with publications in JMSE

Author Response

Thanks for your approval.

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