MARS-Dragonfly creates a force-torque virtual quadrotor model and two-stage predictive allocator that lets reconfigurable drone modules fly stably and agilely, validated in real-world experiments with 0.0896 m average position error.
Autonomous drone racing: A survey
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Dual-gatekeeper integrates robust planning with active exploration under formal safety and budget guarantees, exploring only when verifiable improvement is possible without compromising either.
E2E-Fly supplies an end-to-end training, validation, and deployment stack that lets researchers train differentiable-physics-based policies for six quadrotor tasks and transfer them directly to two physical platforms.
citing papers explorer
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MARS-Dragonfly: Agile and Robust Flight Control of Modular Aerial Robot Systems
MARS-Dragonfly creates a force-torque virtual quadrotor model and two-stage predictive allocator that lets reconfigurable drone modules fly stably and agilely, validated in real-world experiments with 0.0896 m average position error.
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Trajectory Planning for Safe Dual Control with Active Exploration
Dual-gatekeeper integrates robust planning with active exploration under formal safety and budget guarantees, exploring only when verifiable improvement is possible without compromising either.
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E2E-Fly: An Integrated Training-to-Deployment System for End-to-End Quadrotor Autonomy
E2E-Fly supplies an end-to-end training, validation, and deployment stack that lets researchers train differentiable-physics-based policies for six quadrotor tasks and transfer them directly to two physical platforms.