Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehi...

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Detalles Bibliográficos
Autores principales: Doukhi, Oualid, Lee, Deok-Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038595/
https://www.ncbi.nlm.nih.gov/pubmed/33916624
http://dx.doi.org/10.3390/s21072534

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038595/
https://www.ncbi.nlm.nih.gov/pubmed/33916624
http://dx.doi.org/10.3390/s21072534

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