Proximity Operations: Planetary Landing

proximity-operations-planetary-landing

Simulator for Proximity Planetary Landing Operations (including Moon, Mars, Titan, etc.). Find here a gathering of useful Python-binded, ROS-compatible, customizable, real-physics (Bullet/PyBullet physical engine) simulators.

Please cite at least one of the following papers if using these simulators and/or a modified version:

Planetary Landing Simulator: Final EDL

planetary-landing-simulator-final-edl

🫀 Human-Coded (with love) for papers:

1. Learning Transferable Policies for Autonomous Planetary Landing via Deep Reinforcement Learning

Cite as:

@inproceedings{inproceedings, author = {Ciabatti, Giulia and Daftry, Shreyansh and Capobianco, Roberto}, year = {2021}, month = {11}, pages = {}, title = {Learning Transferable Policies for Autonomous Planetary Landing via Deep Reinforcement Learning}, doi = {10.2514/6.2021-4006} }

2. Autonomous Planetary Landing via Deep Reinforcement Learning and Transfer Learning

Cite as:

@inproceedings{inproceedings, author = {Ciabatti, Giulia and Daftry, Shreyansh and Capobianco, Roberto}, year = {2021}, month = {06}, pages = {2031-2038}, title = {Autonomous Planetary Landing via Deep Reinforcement Learning and Transfer Learning}, doi = {10.1109/CVPRW53098.2021.00231} }

Pin-Point Landing: Trajectory Recalculation

pin-point-landing-trajectory-recalculation

3. Deep Reinforcement Learning for Pin-Point Autonomous Lunar Landing: Trajectory Recalculation for Obstacle Avoidance

Cite as:

@inbook{inbook, author = {Ciabatti, Giulia and Spiller, Dario and Daftry, Shreyansh and Capobianco, Roberto and Curti, Fabio}, year = {2023}, month = {06}, pages = {}, title = {Deep Reinforcement Learning for Pin-Point Autonomous Lunar Landing: Trajectory Recalculation for Obstacle Avoidance}, isbn = {978-3-031-25755-1}, doi = {10.1007/978-3-031-25755-1_7} }