16 citations · 30 across the 16 of their papers we have counts for
4 papers · 2 filters
Dual-Arm Tabletop Rearrangement with Movable Stacking and Gap-Aware Push Transfers
Mohammadreza Firoozalizadeh, Zakiye Rostamirad, Arman Barghi +3
Object rearrangement in cluttered tabletop scenes is challenging, especially in wide workspaces where dual-arm systems improve coverage and efficiency. Limited free space often nec…
Skeleton-Guided Geometry-Aware Auto-Labeling for Robotic Grasping: From 4-DoF Learning to 6-DoF Execution
Ali Sabzejou, Farbod Azimmohseni, Mehdi Tale Masouleh +1
Robotic grasping relies on large manually annotated datasets, which are costly to create. We introduce a straight-skeleton-based algorithm for generating two-finger grasp keypoints…
Iterative Grasp Pose Refinement: A Deep Reinforcement Learning Approach for 2D Vision
Amir Arsalan Nematollahi, Shayan Ahmadi, Mehdi Tale Masouleh +1
Developing robots capable of understanding and manipulating objects requires compact, interpretable, and generalizable representations. This work proposes a reinforcement learning-…
Push-Placement: A Hybrid Approach Integrating Prehensile and Non-Prehensile Manipulation for Object Rearrangement
Majid Sadeghinejad, Arman Barghi, Hamed Hosseini +2
Efficient tabletop rearrangement remains challenging due to collisions and the need for temporary buffering when target poses are obstructed. Prehensile pick-and-place provides pre…