Modeling and Solving Multi-Objective Path Planning Problem for Cooperative Cable-Suspended Load Transportation Considering the Time Variable Risk
Cooperative load transportation has the potential to revolutionize the urban logistics industry and can also be utilized in rescue operations following natural disasters. Utilizing cooperative cable-suspended load transportation in such applications involves addressing three problems: static path pl...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10840234/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Cooperative load transportation has the potential to revolutionize the urban logistics industry and can also be utilized in rescue operations following natural disasters. Utilizing cooperative cable-suspended load transportation in such applications involves addressing three problems: static path planning, dynamic path planning, and control. In this article, we aim to tackle the first problem, i.e., static path planning, which is largely separate from the other two tasks. In this regard, we propose a model for the offline path planning of the cooperative cable-suspended load transportation system, including practical constraints. Using the proposed model, we can limit parameters such as the speed and acceleration of UAVs, flight altitude, task completion time, and safety distances between UAVs and obstacles, while minimizing the path length and risk. In addition, we propose an improved hybrid fuzzy particle swarm optimization (PSO) and whale optimization algorithm (WOA) to solve the introduced path planning problem efficiently. Furthermore, a chaotic mutation operator prevents premature convergence in the PSO algorithm. To demonstrate the efficiency of the proposed model and algorithm, three case studies inspired by a fire incident in a forest park have been conducted, and the results have been compared with those of seven other well-known algorithms. |
|---|---|
| ISSN: | 2169-3536 |