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Autor:
Kyle R. Williams, Rachel Schlossman, Daniel Whitten, Joe Ingram, Srideep Musuvathy, James Pagan, Kyle A. Williams, Sam Green, Anirudh Patel, Anirban Mazumdar, Julie Parish
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems. :1-16
This paper presents a technique for trajectory planning based on continuously parameterized high-level actions (motion primitives) of variable duration. This technique leverages deep reinforcement learning (Deep RL) to formulate a policy which is sui
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a3515c6d641373874b2dde515a4e26d
https://doi.org/10.1109/taes.2022.3218496
https://doi.org/10.1109/taes.2022.3218496
