A Hierarchical Trajectory Planning Algorithm for Automated Guided Vehicles in Construction Sites

Round 1

Reviewer 1 Report

To clarify all aspects presented in the above research please complet with:

Exact specifications of the AGV used in experiments, including capacities, dimensions, and any modifications made to suit the working environment.

 Detailed descriptions of the working environment at Guangzhou Baiyun Airport, including types of encountered obstacles and terrain features.

 More information about the industrial computers used and the installed sensors, such as exact specifications and integration methods into the AGV platform.

 Details on sensor calibration and validation to ensure accuracy and reliability of perceived data.

  Detailed explanation of the hierarchical trajectory planning algorithms, including how they are implemented and interact with each other.

 Clarification on how multi-objective evaluation functions for trajectory planning were selected and validated.

More information on the criteria used for representative selection of experimental results and their analysis.

Further explanation of the metrics used for evaluating algorithm performance, such as cost, efficiency, and safety of planned trajectories.

 Additional details on methods used to validate experimental results, such as comparison with other planning algorithms or testing in multiple working environments.

 Extended discussions on limitations and possible future research directions for improving the proposed algorithms.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

This paper proposes a hierarchical trajectory planning algorithm for Automatic Guided Vehicles (AGVs) which integrates coarse planning, considering road constraints and obstacle collision safety, and precise planning that employs small-range sampling, polynomial construction, and collision detection. The effectiveness of the algorithm is demonstrated through experimental validation with a real AGV. I have only a couple of comments and suggestions:

- The authors should discuss or compare with other path planning solutions, such as RRT, Dynamic Window Approach, roadmap methods, and optimization based algorithms such as mpc.

- Since the application is very specific for a particular kind of vehicle, the authors should discuss better the dynamics of that vehicle and its implications on the algorithm, particularly in the context of the precise planning algorithm.

- The authors should also discuss how to apply the obtained trajectory in a trajectory tracking or path-following algorithm. It is not clear from the experimental results section what are the necessary steps to go from the obtained trajectory to vehicle control inputs.

Author Response

Please see the attachment.

Round 2

Reviewer 1 Report

the second review of this revision meet all the requirements.

I propose to accept this scientific article for publication.