[HTML][HTML] Addressing Constraint Coupling and Autonomous Decision-Making Challenges: An Analysis of Large-Scale UAV Trajectory-Planning Techniques
G Huang, M Hu, X Yang, P Lin, Y Wang - Drones, 2024 - mdpi.com
With the increase in UAV scale and mission diversity, trajectory planning systems faces
more and more complex constraints, which are often conflicting and strongly coupled …
more and more complex constraints, which are often conflicting and strongly coupled …
Heuristic task scheduling on heterogeneous UAVs: a combinatorial optimization approach
K Li - Journal of Systems Architecture, 2023 - Elsevier
A fleet of unmanned aerial vehicles (UAVs) provide a new and unique type of distributed
computing paradigm and platform. This is a distributed computing environment with mobile …
computing paradigm and platform. This is a distributed computing environment with mobile …
Deep Reinforcement Learning for Job Scheduling and Resource Management in Cloud Computing: An Algorithm-Level Review
Y Gu, Z Liu, S Dai, C Liu, Y Wang, S Wang… - arXiv preprint arXiv …, 2025 - arxiv.org
Cloud computing has revolutionized the provisioning of computing resources, offering
scalable, flexible, and on-demand services to meet the diverse requirements of modern …
scalable, flexible, and on-demand services to meet the diverse requirements of modern …
Multi-UAV reconnaissance mission planning via deep reinforcement learning with simulated annealing
Unmanned aerial vehicles (UAVs) are widely used in reconnaissance missions due to their
autonomy and flexibility. Efficient mission planning for multiple UAVs is crucial for tasks such …
autonomy and flexibility. Efficient mission planning for multiple UAVs is crucial for tasks such …
[HTML][HTML] Container Scheduling Algorithms for Distributed Cloud Environments
H Chen, C Shen, X Qiu, C Cheng - Processes, 2024 - mdpi.com
Due to the difficulty of existing container scheduling algorithms to adapt to large-scale
complex scenarios and meet the diverse application and load requirements, this study …
complex scenarios and meet the diverse application and load requirements, this study …
Generative AI-Augmented Graph Reinforcement Learning for Adaptive UAV Swarm Optimization
Unmanned aerial vehicles (UAVs) are essential for providing communication and
computation services in disaster recovery scenarios where traditional infrastructure is …
computation services in disaster recovery scenarios where traditional infrastructure is …
Deep reinforcement learning assisted memetic scheduling of drones for railway catenary deicing
Icy rainfall and snowfall in 2024 Spring Festival struck the high-speed railway catenary
systems and caused serious traffic disruptions in central and eastern China. Deicing drones …
systems and caused serious traffic disruptions in central and eastern China. Deicing drones …
[HTML][HTML] Learning Improvement Heuristics for Multi-Unmanned Aerial Vehicle Task Allocation
B Fan, Y Bo, X Wu - Drones, 2024 - mdpi.com
Nowadays, small UAV swarms with the capability of carrying inexpensive munitions have
been highly effective in strike missions against ground targets on the battlefield. Effective …
been highly effective in strike missions against ground targets on the battlefield. Effective …
[HTML][HTML] A Deep Q-Learning Based UAV Detouring Algorithm in a Constrained Wireless Sensor Network Environment
Unmanned aerial vehicles (UAVs) play a crucial role in various applications, including
environmental monitoring, disaster management, and surveillance, where timely data …
environmental monitoring, disaster management, and surveillance, where timely data …
Hierarchical Reinforcement Learning for Swarm Confrontation with High Uncertainty
Q Wu, K Liu, L Chen, J Lü - arXiv preprint arXiv:2406.07877, 2024 - arxiv.org
In swarm robotics, confrontation including the pursuit-evasion game is a key scenario. High
uncertainty caused by unknown opponents' strategies and dynamic obstacles complicates …
uncertainty caused by unknown opponents' strategies and dynamic obstacles complicates …