Convex-Neural RRT* uses neural guidance to predict waypoint regions, extracts convex sampling areas from them, and reports 30-75% faster planning than other neural RRT* methods with ~5% shorter paths and >99% success rate on 18 maps.
Path Planning for Unmanned Aerial Vehicles in Complex Environment Based on an Improved Continuous Ant Colony Optimisation
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Convex-Neural RRT*: Fast and Reliable Learning-Guided Sampling for High-Quality Robot Path Planning
Convex-Neural RRT* uses neural guidance to predict waypoint regions, extracts convex sampling areas from them, and reports 30-75% faster planning than other neural RRT* methods with ~5% shorter paths and >99% success rate on 18 maps.