Push-Placement: A Hybrid Approach Integrating Prehensile and Non-Prehensile Manipulation for Object Rearrangement

TL;DR

This paper introduces push-placement, a hybrid manipulation primitive combining grasping and pushing to improve efficiency in tabletop object rearrangement, reducing travel costs and avoiding complex buffering.

Contribution

It presents a novel hybrid action primitive integrated into a physics-based planner, demonstrating improved efficiency over traditional methods in simulated rearrangement tasks.

Findings

Push-placement reduces manipulator travel by up to 11.12%.

It outperforms baseline MCTS in efficiency.

Hybrid manipulation primitives enhance long-horizon rearrangement performance.

Abstract

Efficient tabletop rearrangement remains challenging due to collisions and the need for temporary buffering when target poses are obstructed. Prehensile pick-and-place provides precise control but often requires extra moves, whereas non-prehensile pushing can be more efficient but suffers from complex, imprecise dynamics. This paper proposes push-placement, a hybrid action primitive that uses the grasped object to displace obstructing items while being placed, thereby reducing explicit buffering. The method is integrated into a physics-in-the-loop Monte Carlo Tree Search (MCTS) planner and evaluated in the PyBullet simulator. Empirical results show push-placement reduces the manipulator travel cost by up to 11.12% versus a baseline MCTS planner and 8.56% versus dynamic stacking. These findings indicate that hybrid prehensile/non-prehensile action primitives can substantially improve efficiency in long-horizon rearrangement tasks.