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Imitative Planning using Conditional Normalizing Flow
[article]
2022
arXiv
pre-print
A popular way to plan trajectories in dynamic urban scenarios for Autonomous Vehicles is to rely on explicitly specified and hand crafted cost functions, coupled with random sampling in the trajectory space to find the minimum cost trajectory. Such methods require a high number of samples to find a low-cost trajectory and might end up with a highly suboptimal trajectory given the planning time budget. We explore the application of normalizing flows for improving the performance of trajectory
arXiv:2007.16162v3
fatcat:zmd2gaykkvdcbbeywrnqsr4t4e