Q value learning in the area including targets and a coordination mechanism (CM) that selects the proper actions to search and isolate the targets from the surrounding objects, even in the condition of targets invisible. Our method is inspired by the working memory mechanism of human brain and can grasp any target object shown through the image and has good generality in application. Experimental results in simulation and real-world show that our method achieved the best performance compared with the baselines in finding the unknown target objects from the cluttered environment with only one demonstrated target RGB-D image and had the high efficiency of grasping under the synergies of push and grasp actions.">

PLOT: Human-Like Push-Grasping Synergy Learning in Clutter With One-Shot Target Recognition (original) (raw)

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