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PartialBiGrasp: A dual-arm grasping framework that infers hidden local geometry from partial views

PartialBiGrasp is a dual-arm grasp generation framework that operates directly on partial point cloud observations. It implicitly learns geometric features through a convolutional occupancy network to reason about graspability, collision-free contact regions, and object thickness. Based on this, the method generates force-closure-compliant grasp pairs and uses sampling-based optimization to correct for ambiguity caused by incomplete geometry. The authors evaluated the method using analytical force-closure metrics, large-scale simulation experiments, and noisy partial point clouds on a real robot.

Part of the event: PartialBiGrasp: Dual-arm Grasp Generation from Partial Point Clouds

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