Virtues of Ordered Chaos: Planning with Topple Actions in Tabletop Stack Rearrangement
Hao Lu, Rahul Shome

TL;DR
This paper introduces a novel planning approach for tabletop stack rearrangement that incorporates topple actions, leading to more efficient object manipulation strategies in automation.
Contribution
It presents a new aggregating gadget for topple actions and models the planning problem as a pebble motion variant, demonstrating improved efficiency in simulations.
Findings
Topple actions can significantly reduce the number of steps in rearrangement plans.
The pebble motion abstraction effectively models combined pick-and-place and topple actions.
Simulation results show faster execution with topple-inclusive plans.
Abstract
Efficient object manipulation strategies have significant impact in automation applications. In this work, the stack rearrangement in tabletop settings is studied, with a focus on augmenting the task planning domain with richer nonprehensile aggregating actions, in particular the toppling of objects from a stack to the table. Toppling can compress long sequences of intermediate relocations. Computed plans need to interleave pick-and-place actions with topple throughout its plan based on the problem. In order to generate the task plan and model an abstraction to compute solutions that include both pick-and-place and topple actions, a novel aggregating gadget for topple is introduced. Using this directed graphical abstraction, candidate task plan computation becomes a variant of the pebble motion problem, treating objects as pebbles. Benchmarks are then reported in a IsaacSim-based…
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