Lunar Rover Analogue Mission Deployments

2014 ◽  
Author(s):  
Peter D. Visscher ◽  
Daniel B. Woolley
Keyword(s):  
Lunar Rover

Lunar Rover Wheel-Terrain Interaction Model for Climbing-up-Slope Based on Terramechanics

ROBOT ◽  
2010 ◽  
Vol 32 (1) ◽  
pp. 70-76 ◽  
Author(s):  
Zhen JIAO ◽  
Haibo GAO ◽  
Zongquan DENG ◽  
Liang DING
Keyword(s):  
Interaction Model ◽  
Lunar Rover

The role of terrain modeling in lunar rover simulation

SIMULATION ◽  
1993 ◽  
Vol 61 (1) ◽  
pp. 60-68
Author(s):  
Niranjan S. Rao ◽  
Matthew H. Appleby
Keyword(s):  
Terrain Modeling ◽  
Lunar Rover

scholarly journals Learning-Based End-to-End Path Planning for Lunar Rovers with Safety Constraints

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 796
Author(s):  
Xiaoqiang Yu ◽  
Ping Wang ◽  
Zexu Zhang
Keyword(s):  
Path Planning ◽  
Lunar Surface ◽  
Training Environment ◽  
Lunar Rover ◽  
Reward Function ◽  
Safety Constraints ◽  
Planning Algorithm ◽  
Lunar Rovers ◽  
End To End ◽  
Path Planning Algorithm

Path planning is an essential technology for lunar rover to achieve safe and efficient autonomous exploration mission, this paper proposes a learning-based end-to-end path planning algorithm for lunar rovers with safety constraints. Firstly, a training environment integrating real lunar surface terrain data was built using the Gazebo simulation environment and a lunar rover simulator was created in it to simulate the real lunar surface environment and the lunar rover system. Then an end-to-end path planning algorithm based on deep reinforcement learning method is designed, including state space, action space, network structure, reward function considering slip behavior, and training method based on proximal policy optimization. In addition, to improve the generalization ability to different lunar surface topography and different scale environments, a variety of training scenarios were set up to train the network model using the idea of curriculum learning. The simulation results show that the proposed planning algorithm can successfully achieve the end-to-end path planning of the lunar rover, and the path generated by the proposed algorithm has a higher safety guarantee compared with the classical path planning algorithm.

Cryogenic Vacuum Testing of Lunar Rover Drivetrain

2018 ◽  
Author(s):  
Perry Edmundson ◽  
Peter Visscher ◽  
Josh Newman ◽  
Joseph O’Connell ◽  
Martin Picard
Keyword(s):  
Lunar Rover ◽  
Cryogenic Vacuum ◽  
Vacuum Testing

Double Closed-Loop Motor Modeling and Analysis for Lunar Rover Simulation

2012 ◽  
Vol 472-475 ◽  
pp. 1971-1976 ◽  
Author(s):  
Wei Dong Huang ◽  
Hong Kui Feng ◽  
Jin Song Bao ◽  
You Sheng Xu
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Dynamics Simulation ◽  
Motor Drive ◽  
Modeling And Analysis ◽  
Lunar Rover ◽  
System A ◽  
Drive Control ◽  
Body Dynamics ◽  
Multi Body

Motor drive control is the major study field in the development of lunar rover. Based on the double-closed DC loop adjustable-speed system, a motor drive simulation module using a position recursive PID control algorithm is developed, which is integrated into the multi-body dynamics simulation system, to carry out the whole lunar rover simulation. And the cruise process of lunar rover locomotion in the complex lunar terrain is simulated in a virtual environment.

Estimation of the Strength of the Lunar Soil by the Depth of the Lunar Rover Wheel Tracks

2021 ◽  
Vol 55 (4) ◽  
pp. 285-308
Author(s):  
A. T. Basilevsky ◽  
M. I. Malenkov ◽  
V. A. Volov ◽  
A. M. Abdrakhimov ◽  
N. A. Kozlova ◽  
...  
Keyword(s):  
Lunar Soil ◽  
Lunar Rover
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