Joint Optimization of Path Planning and Cooperative Strategy for UAV-UGV Deliveryopen access
- Authors
- Jang, Gihyeon; Lee, Kisong
- Issue Date
- Nov-2025
- Publisher
- IEEE
- Keywords
- convex optimization; cooperative strategy; path planning; Unmanned aerial vehicle; unmanned ground vehicle
- Citation
- IEEE Transactions on Intelligent Transportation Systems, v.26, no.11, pp 20176 - 20186
- Pages
- 11
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE Transactions on Intelligent Transportation Systems
- Volume
- 26
- Number
- 11
- Start Page
- 20176
- End Page
- 20186
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/58872
- DOI
- 10.1109/TITS.2025.3589541
- ISSN
- 1524-9050
1558-0016
- Abstract
- In this study, we consider a new cooperative unmanned aerial vehicle (UAV)–unmanned ground vehicle (UGV) delivery framework, where the UAV picks up parcels and the UGV drops off the parcels it is carrying to share the workload associated with picking up and delivering parcels. Because of the limited load capacity of the UAV, it can unload the parcels onto the UGV or at the destination. We mathematically formulate this system model and aim to optimize the horizontal and vertical trajectories of the two vehicles, as well as the binary indicators representing pickup, drop-off, and cooperation, to minimize the total mission completion time. To handle the nonconvexity of the formulated problem, we utilize a successive convex approximation technique to transform nonconvex constraints into convex sets. Additionally, we apply a penalty convex–concave procedure to relax the binary indicators to achieve continuous values for optimizations while preserving their binary characteristics. Finally, we propose a cooperative algorithm to iteratively derive suboptimal solutions from the relaxed convex problem. The simulation results demonstrate that the proposed scheme effectively optimizes both path planning and the cooperation strategy, enabling the UAV to drop off the parcels it carries onto the UGV at the optimal location. This approach significantly reduces delivery time and outperforms the baseline schemes in various environments. © 2000-2011 IEEE.
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