2022
Autonomous State-Based Flipper Control for Articulated Tracked Robots in Urban Environments
RA-L 2022
We demonstrate a hybrid approach to autonomous flipper control, focusing on a fusion of hard-coded and learned knowledge. The result is a sample-efficient and modifiable control structure that can be used in conjunction with a mapping/navigation stack. The backbone of the control policy is formulate