A three-stage grasping-picking-stacking curriculum with a redesigned reward reduces training time by about 40 percent and improves block-stacking success by roughly 10 percent over direct learning in the CausalWorld simulator.
of Aerospace & Mechanical Engineering University of Southern California Los Angeles, USA xinruiw@usc.edu Yan Jin* Dept
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Knowledge capture, adaptation and composition (KCAC): A framework for cross-task curriculum learning in robotic manipulation
A three-stage grasping-picking-stacking curriculum with a redesigned reward reduces training time by about 40 percent and improves block-stacking success by roughly 10 percent over direct learning in the CausalWorld simulator.