首页|Findings from University of California Berkeley Has Provided New Data on Robotics [Contact-rich se(3)-equivariant Robot Manipulation Task Learning Via Geometric Impedance Control]
Findings from University of California Berkeley Has Provided New Data on Robotics [Contact-rich se(3)-equivariant Robot Manipulation Task Learning Via Geometric Impedance Control]
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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.
BerkeleyCaliforniaUnited StatesNorth and Central AmericaEmerging TechnologiesMachine LearningRobotRoboticsUniversity of California Berkeley
NETL
NSTL
IEEE
