Published October 20, 2025
| Version v1
Conference paper
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Learning Coordinated Pushing Actions for Grasp-Based Occluded Object Retrieval in Cluttered Environments
Authors/Creators
Description
We propose a push-to-grasp framework that coordinates
pushing and grasping actions through three Deep Q-Networks
orchestrated by a perception-based oracle module, to
achieve occluded object retrieval from a cluttered
environment. The networks are trained through Deep
Reinforcement Learning (DRL) in simulation, and then
deployed on a robot, successfully executing retrieval tasks
in the real world.
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