2026· Proceedings of the 1st International Conference on Smart System Design, Application and Mechatronics· pp. 154-164· 0 citations· 9 references
Abstract
: In the fields of dynamic target protection and autonomous system cooperative control, achieving the optimal allocation of limited resources through intelligent decision-making has always been a core challenge in engineering practice and theoretical research. This study focuses on the complex problem of UAV swarms using smoke grenades to jam tracking targets in three-dimensional space, aiming to extend the target's movement time. A complex system model integrating multi-body dynamic coupling, spatiotemporal resource allocation, and environmental uncertainty adaptation is constructed. By defining the discrete degree quantitative index of target C, the dual-objective optimization of UAV utilization rate and smoke grenade effectiveness is realized based on the reinforcement learning DDPG algorithm.
This paper investigates the cooperative task allocation problem for heterogeneous multi-UAV clusters under complex environmental constraints. Targeting practical constraints including multi-airport deployment, diversified heterogeneous UAV configurations and diverse operational mission requirements, this paper formulat...
Xiao-Bo Ma, Lei-Gang Hu, Yang-Yang Sun et al.· 2026 2nd International Confe...· 0 citations
Simulations show the SAC-based approach outperforms benchmarks in task completion rate, energy consumption, and convergence, and validate the maximum entropy mechanism's effectiveness in enhancing exploration and generalization in UAV-assisted ISAC environments.
Multi-UAV multi-sensor cooperative detection is critical for situational awareness in complex environments with stationary known targets. To overcome the shortcomings of existing task allocation models in fine-grained cooperation, stealth constraints, and large-scale optimization, this paper proposes a new offline miss...
Bo-Xuan Wang, Kun Zhang, Shuang Zhao et al.· Aerospace· 0 citations
This review examines approaches to energy optimization of UAVs using algorithms and artificial intelligence (AI) to optimize energy efficiency of trajectory planning, adaptive speed control, battery management in mission planning, and navigation that accounts for environmental characteristics.
Wojciech Skarka, Rukhseena Ashfaq, Arun Winglin Amaladoss et al.· Energies· 0 citations
To address uneven population distribution and premature convergence of the standard Salp Swarm Algorithm (SSA) in grid-connected microgrid scheduling, this study develops an Improved Salp Swarm Algorithm (ISSA). Sine chaotic mapping is used for population initialization. A distance-adaptive follower update is then empl...
Qi Chen, Tao Ma, Li Song et al.· Processes· 0 citations
The improved algorithm is compared with five mainstream swarm intelligence algorithms on ten benchmark functions to verify its effectiveness and the simulation results of three-dimensional trajectory planning using the improved algorithm and other swarm intelligence algorithms are presented, which demonstrate the super...
