Path planning for asteroid hopping rovers with pre-trained deep reinforcement learning architectures-Reference-Cited by-同舟云学术

Path planning for asteroid hopping rovers with pre-trained deep reinforcement learning architectures

Published:2020-06 Issue: Volume:171 Page:265-279
ISSN:0094-5765
Container-title:Acta Astronautica
language:en
Short-container-title:Acta Astronautica

Author:

Jiang Jianxun,Zeng Xiangyuan,Guzzetti Davide,You Yuyang

Funder

Beijing Institute of Technology

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Aerospace Engineering

Reference38 articles.

1. Investigation on the development of deep space exploration;Wu;Sci. China Technol. Sci.,2012

2. Detection of the YORP effect for small asteroids in the Karin cluster;Carruba,2016

3. Micro-hopping robot for asteroid exploration;Yoshimitsu;Acta Astronaut.,2003

4. Astrobiology and the possibility of life on Earth and elsewhere;Cottin;Space Sci. Rev.,2017

5. Asteroid Mining: Mineral Resources in Undifferentiated Bodies from the Chemical Composition of Carbonaceous Chondrites, Assessment and Mitigation of Asteroid Impact Hazards;Martínez-Jiménez,2017

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