NaviSlim uses a gated slimmable architecture to dynamically scale neural model complexity and onboard sensor power for context-aware navigation in micro-drones, reporting 57-92% average model reduction and 61-80% sensor utilization in AirSim simulations versus static full-complexity baselines.
A formal basis for the heuristic determination of minimum cost paths,
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Introduces an efficient B-spline kinodynamic replanning framework for quadrotors combining EBK search for minimum-effort feasible trajectories with elastic optimization to refine control points.
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NaviSlim: Adaptive Context-Aware Navigation and Sensing via Dynamic Slimmable Networks
NaviSlim uses a gated slimmable architecture to dynamically scale neural model complexity and onboard sensor power for context-aware navigation in micro-drones, reporting 57-92% average model reduction and 61-80% sensor utilization in AirSim simulations versus static full-complexity baselines.
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An Efficient B-spline-Based Kinodynamic Replanning Framework for Quadrotors
Introduces an efficient B-spline kinodynamic replanning framework for quadrotors combining EBK search for minimum-effort feasible trajectories with elastic optimization to refine control points.