Efficient Data Collection for Robotic Manipulation via Compositional Generalization

arXiv:2403.05110v1 Announce Type: cross
Abstract: Data collection has become an increasingly important problem in robotic manipulation, yet there still lacks much understanding of how to effectively collect data to facilitate broad generalization. Recent works on large-scale robotic data collection typically vary a wide range of environmental factors during data collection, such as object types and table textures. While these works attempt to cover a diverse variety of scenarios, they do not explicitly account for the possible compositional abilities of policies …

arxiv collection cs.ai cs.lg cs.ro data data collection manipulation robotic robotic manipulation type via