Multi-UAV Deployment in Obstacle-Cluttered Environments with LOS Connectivity
July 29, 2025 Β· Declared Dead Β· π IEEE/RJS International Conference on Intelligent RObots and Systems
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yuda Chen, Shuaikang Wang, Jie Li, Meng Guo
arXiv ID
2507.21772
Category
cs.RO: Robotics
Citations
1
Venue
IEEE/RJS International Conference on Intelligent RObots and Systems
Last Checked
6 months ago
Abstract
A reliable communication network is essential for multiple UAVs operating within obstacle-cluttered environments, where limited communication due to obstructions often occurs. A common solution is to deploy intermediate UAVs to relay information via a multi-hop network, which introduces two challenges: (i) how to design the structure of multihop networks; and (ii) how to maintain connectivity during collaborative motion. To this end, this work first proposes an efficient constrained search method based on the minimumedge RRT? algorithm, to find a spanning-tree topology that requires a less number of UAVs for the deployment task. Then, to achieve this deployment, a distributed model predictive control strategy is proposed for the online motion coordination. It explicitly incorporates not only the inter-UAV and UAVobstacle distance constraints, but also the line-of-sight (LOS) connectivity constraint. These constraints are well-known to be nonlinear and often tackled by various approximations. In contrast, this work provides a theoretical guarantee that all agent trajectories are ensured to be collision-free with a teamwise LOS connectivity at all time. Numerous simulations are performed in 3D valley-like environments, while hardware experiments validate its dynamic adaptation when the deployment position changes online.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Robotics
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
π
π
The Cartographer
A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles
π
π
The Cartographer
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
π
π
The Cartographer
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
R.I.P.
π»
Ghosted
Learning agile and dynamic motor skills for legged robots
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted