Coordinated quadrotor swarms operating in cluttered environments must simultaneously achieve robust low-level stabilization and high-level, constraint-aware motion generation for safe formation flight. This paper proposes a hierarchical RL-SMC control framework for leader–follower quadrotor swarms navigating three-dimensional obstacle-rich workspaces that include explicit no-fly regions. At the low level, a boundary-layer sliding mode attitude controller provides disturbance-tolerant tracking of commanded Euler references, while a mid-level translational loop converts bounded velocity commands into physically feasible thrust and attitude setpoints. At the high level, a reinforcement learning (RL) policy learns to generate bounded planar acceleration references for the leader, using an observation and reward design that explicitly accounts for both the leader state and the worst-case clearance of the formation footprint to obstacles and restricted zones. The followers track leader-aligned V-shape offsets, enabling formation motion without direct learning-based actuation. Simulation results in a constrained 3D environment demonstrate goal-reaching while maintaining formation integrity and satisfying safety margins, with smooth bounded guidance actions and no collisions or no-fly violations. The proposed architecture combines the adaptability of RL with the robustness properties of variable-structure control in a modular, safety-oriented swarm control stack.
Ayman Abdallah, Y. Alqudsi, M. Mohiuddin· International Workshop on Va...· 0 citations
Timely and dependable information exchange is essential for large-scale unmanned aerial vehicle (UAV) swarms to coordinate under their fast motion, intermittent links, and limited energy on board. However, swarm deployments increasingly must contend with spectrum contention and jamming, as well as a lack of dependable infrastructure, which can reveal the shortcomings of traditional radio-frequency (RF) networking. This paper presents a synthesized overview of communication technologies and networking architectures for UAV swarm operations in FANETs. Representative studies were identified by a structured search and screening process across major venues of scholarly output, which are synthesized using a cross-layer lens including physical links, medium access, routing, information-centric networking, learning-enabled adaptation, and security. In this article, We compare RF/cellular with emerging high-capacity links including millimeter-wave and free-space optical communication, and then show how routing/indirection and content/function-centric paradigms (NDN/NFN) can mitigate fragility imposed by reliance on brittle end-to-end paths. Lastly, we analyse learning-based control (especially multi-agent reinforcement learning) for communication-aware mobility and resources management, as well as security approaches for contested settings. The resulting design perspective highlights recurring trade-offs among reliability, latency, throughput, energy, and integrity, and identifies practical research directions toward more robust and deployable swarm communication systems.
Azzam Almekhlafi, Y. Alqudsi· 2026 6th International Confe...· 0 citations
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