An end-to-end vision-based framework enables UAVs to traverse complex irregular gaps in unseen environments by mapping depth images to SE(3) control commands using differentiable simulation.
Learning agile flights through narrow gaps with varying angles using onboard sensing
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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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Vision-Based End-to-End Learning for UAV Traversal of Irregular Gaps via Differentiable Simulation
An end-to-end vision-based framework enables UAVs to traverse complex irregular gaps in unseen environments by mapping depth images to SE(3) control commands using differentiable simulation.
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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.