Abstract
New research on Robotics is the subject of a report. According to news reporting out of Berkeley, California, by NewsRx editors, research stated, "This letter presents a differential geometric control approach that leverages SE(3) group invariance and equivariance to increase transferability in learning robot manipulation tasks that involve interaction with the environment. Specifically, we employ a control law and a learning representation framework that remain invariant under arbitrary SE(3) transformations of the manipulation task definition." Financial support for this research came from National Research Foundation of Korea.
NETL
NSTL
IEEE