167 citations · 367 across the 27 of their papers we have counts for
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cs.RO2023
Sim-MEES: Modular End-Effector System Grasping Dataset for Mobile Manipulators in Cluttered Environments
Juncheng Li, David J. Cappelleri
In this paper, we present Sim-MEES: a large-scale synthetic dataset that contains 1,550 objects with varying difficulty levels and physics properties, as well as 11 million grasp l…
cs.RO2023★ 18 cited
Sim-Suction: Learning a Suction Grasp Policy for Cluttered Environments Using a Synthetic Benchmark
Juncheng Li, David J. Cappelleri
This paper presents Sim-Suction, a robust object-aware suction grasp policy for mobile manipulation platforms with dynamic camera viewpoints, designed to pick up unknown objects fr…