TY  - JOUR
AU  - Li, Quan
AU  - Shen, Zitong
AU  - Ding, Qingwen
AU  - Liu, Yaxuan
AU  - Dai, Rui
AU  - Zhou, Jin
AU  - Ni, Yiyang
PY  - 2026
DA  - 2026/09/26
TI  - Communication Topology Resilience-Guided Optimization for Multi-UAV Cooperative Planning
JO  - Aerospace Engineering Communications
T2  - Aerospace Engineering Communications
JF  - Aerospace Engineering Communications
VL  - 1
IS  - 3
SP  - 128
EP  - 136
DO  - 10.62762/AEC.2026.595594
UR  - https://www.icck.org/article/abs/AEC.2026.595594
KW  - multi-UAV swarm
KW  - cooperative planning
KW  - communication topology resilience
KW  - algebraic connectivity
KW  - simulated annealing
AB  - This paper studies cooperative mission planning for multi-unmanned aerial vehicle (UAV) swarms in obstacle-cluttered environments, with particular attention to mission feasibility and communication-topology resilience. Considering that task assignment and waypoint selection directly affect the inter-UAV communication graph, a communication topology resilience-guided (CTR) method is proposed by introducing algebraic connectivity as an explicit topology metric. The method first performs topology-guided one-to-one task assignment using simulated annealing, jointly considering normalized distance, obstacle risk, and algebraic connectivity. It then selects topology-aware key waypoints according to path length, obstacle risk, isolation penalty, and conflict-neighborhood cost, followed by path stitching and wait-insertion-based temporal conflict correction. Compared with prioritized planning (PP) and genetic algorithm (GA) baselines, CTR achieves a higher mission success rate and stronger algebraic connectivity, while substantially improving communication connectivity over the topology-ablated variant with essentially the same success rate. Monte Carlo simulations under different swarm sizes and obstacle densities verify the effectiveness of the proposed method.
SN  - 3071-1967
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Li2026Communicat,
  author = {Quan Li and Zitong Shen and Qingwen Ding and Yaxuan Liu and Rui Dai and Jin Zhou and Yiyang Ni},
  title = {Communication Topology Resilience-Guided Optimization for Multi-UAV Cooperative Planning},
  journal = {Aerospace Engineering Communications},
  year = {2026},
  volume = {1},
  number = {3},
  pages = {128-136},
  doi = {10.62762/AEC.2026.595594},
  url = {https://www.icck.org/article/abs/AEC.2026.595594},
  abstract = {This paper studies cooperative mission planning for multi-unmanned aerial vehicle (UAV) swarms in obstacle-cluttered environments, with particular attention to mission feasibility and communication-topology resilience. Considering that task assignment and waypoint selection directly affect the inter-UAV communication graph, a communication topology resilience-guided (CTR) method is proposed by introducing algebraic connectivity as an explicit topology metric. The method first performs topology-guided one-to-one task assignment using simulated annealing, jointly considering normalized distance, obstacle risk, and algebraic connectivity. It then selects topology-aware key waypoints according to path length, obstacle risk, isolation penalty, and conflict-neighborhood cost, followed by path stitching and wait-insertion-based temporal conflict correction. Compared with prioritized planning (PP) and genetic algorithm (GA) baselines, CTR achieves a higher mission success rate and stronger algebraic connectivity, while substantially improving communication connectivity over the topology-ablated variant with essentially the same success rate. Monte Carlo simulations under different swarm sizes and obstacle densities verify the effectiveness of the proposed method.},
  keywords = {multi-UAV swarm, cooperative planning, communication topology resilience, algebraic connectivity, simulated annealing},
  issn = {3071-1967},
  publisher = {Institute of Central Computation and Knowledge}
}