A-Star (A*) with Map Processing for the Global Path Planning of Autonomous Underwater and Surface Vehicles Operating in Large Areas
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper employs A-star (A*) with map processing for global path planning of autonomous underwater and surface vehicles operating in large areas. In general, this method sounds interesting and my comments are listed as follows:
1. Ensure the consistency of specific nouns. For example, “UUV” and “USV” in the abstract are inconsistent with “AUV” and “ASV” in the main text.
2. The literature review is somewhat inadequate. The article briefly introduces existing path planning algorithms in the introduction and related work sections, but lacks a comprehensive review of the latest literature, especially a lack of in-depth analysis of related research in recent years on the improvement of the A algorithm. This makes the article seem inadequate when discussing its innovation.
3. The pictures in the article are relatively blurry, especially those in real environments, which need to maintain a certain clarity to demonstrate authenticity.
4. The explanation of the simulation environment in the third part needs to be more detailed. The current article does not describe this part enough, making it difficult to understand.
5. The article uses too many words to describe the A-star algorithm, which is a bit colloquial. A-star is a very famous path planning algorithm, and it should be possible to express the meaning of the A-star basic algorithm by adding formulas or using certain schematic diagrams.
6. The process of using A-star to process the map in this article is also too verbal, and it can be appropriately summarized in the form of a formula. At the same time, the overall solution process should be added in the form of pseudocode or flowchart to help intuitively and concisely understand the method process of this article.
7. The information displayed in the process result map and parameter table of A-star processing map is not sufficient. Detailed description should be added, and the parameters in the data table should be increased.
8. Other related path planning methods are suggested to be added in the literature review part, e.g., reinforcement learning, A cross-platform deep reinforcement learning model for autonomous navigation without global information in different scenes, Control Engineering Practice 150, 105991
Comments on the Quality of English LanguageMinor editing of English language is required.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsSpecific Comments
-Authors failed to state in clear terms the objectives of the manuscript. What are the specific research objectives of this manuscript?
-Page 4; Line 115; Change the statement, “This chapter…” to “This section…”
-Page 5; The texts in Figure 2 (a) and (b) are not readable. Authors should make the write-ups readable.
-No performance evaluation of the proposed approach with recent related works (2022-2024) was carried out in the manuscript. Are there no recent related works? Authors should check recent works and compare their results with existing works. There are so many recent works with promising results.
Some Suggested works
Mehmood, D., Ali, A., Ali, S., Kulsoom, F., Chaudhry, H. N., & Haider, A. Z. U. (2024, January). A Novel Hybrid Genetic and A-star Algorithm for UAV Path Optimization. In 2024 IEEE 1st Karachi Section Humanitarian Technology Conference (KHI-HTC) (pp. 1-5). IEEE.
Zhang, D., Chen, C., & Zhang, G. (2024, March). AGV path planning based on improved A-star algorithm. In 2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (Vol. 7, pp. 1590-1595). IEEE.
Li, J., Xiong, X., & Yang, Y. (2023, September). A Method of UAV Navigation Planning Based on ROS and Improved A-star Algorithm. In 2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS) (pp. 1-5). IEEE.
-There are several backward references [4], [5], [6], [7], etc. Authors should look for recent works and update the references.
-Overall, the manuscript should be thoroughly rewritten to address these salient points and omissions to substantiate its novelty.
Comments for author File: Comments.pdf
Thorough editing should be carried out on the manuscript.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsIn the paper, the authors present a novel approach that integrates image processing of the map prior to applying the A* algorithm for path planning, specifically targeting autonomous operations of unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs) in complex aquatic environments. The A* algorithm is well-known for path planning due to its ability to find near-optimal paths and effectively avoid obstacles. However, a key limitation of this method is its high computational cost.
The paper is well-structured, clearly written, and effectively demonstrates the application of the method and the results obtained.
In my opinion, there are a few areas where the authors could enhance the manuscript:
1 1. As described in the paper, this optimal path planning algorithm requires significant computational resources. The tests conducted are in a simulation environment, where image processing techniques were applied post-processing to prepare the occupancy grid and reduce the computational burden of path calculation. My question is: Could this method be viable for real-time applications, given the high computational demands?
2. Consequently, it is essential to have hardware capable of meeting these requirements. How do the authors envision the integration of such hardware on board UUVs or USVs for autonomous operations, considering the potential constraints on processing power?
3. Additionally, considering autonomous operations, could the sea conditions pose challenges to the algorithm’s ability to estimate the optimal path? For instance, how would surface waves or currents affect the algorithm’s performance in real-world scenarios?
These points, if addressed, would further strengthen the paper's contribution to the field.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe authors have addressed all my comments.
Comments on the Quality of English LanguageMinor editing of English language is required.
Reviewer 3 Report
Comments and Suggestions for AuthorsIn this paper, the authors introduce a novel approach that integrates image processing of the map before the application of the A* algorithm for path planning, specifically designed for autonomous operations of unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs) in complex aquatic environments. The A* algorithm is widely recognized for its effectiveness in path planning due to its ability to identify near-optimal paths and efficiently avoid obstacles. However, one of the primary limitations of this method is its substantial computational cost.
The paper is well-organized, clearly written, and successfully demonstrates the application of the proposed method, along with the results obtained. Having reviewed the latest version of the manuscript, I believe it is suitable for publication.
