Real-Time Motion Planning Framework for Autonomous Vehicles with Learned Committed Trajectory Distribution
Minsoo Kim,Seho Shin,Joonwoo Ahn,Jaeheung Park,Minsoo Kim,Seho Shin,Joonwoo Ahn,Jaeheung Park
This study proposes a realtime motion planning framework that leverages the prediction of a portion of the optimal trajectory for sampling-based anytime planning algorithms. Existing algorithms predict the entire optimal path and bias random samples toward it for fast path planning. However, these algorithms may not be suitable for realtime frameworks because the bias-sampling strategy should cons...
