# Object Reconfiguration with Simulation-Derived Feasible Actions

## TL;DR

This paper introduces a simulation-based planning approach for 3D object reconfiguration that automatically discovers feasible actions through physics simulation, eliminating manual encoding and improving planning efficiency.

## Contribution

It presents a novel method embedding a physics simulator within a motion planner to implicitly determine valid actions, streamlining the reconfiguration process.

## Key findings

- Successfully generates physically valid rearrangement trajectories
- Reduces manual effort in specifying action semantics
- Works across diverse 3D object reconfiguration scenarios

## Abstract

3D object reconfiguration encompasses common robot manipulation tasks in which a set of objects must be moved through a series of physically feasible state changes into a desired final configuration. Object reconfiguration is challenging to solve in general, as it requires efficient reasoning about environment physics that determine action validity. This information is typically manually encoded in an explicit transition system. Constructing these explicit encodings is tedious and error-prone, and is often a bottleneck for planner use. In this work, we explore embedding a physics simulator within a motion planner to implicitly discover and specify the valid actions from any state, removing the need for manual specification of action semantics. Our experiments demonstrate that the resulting simulation-based planner can effectively produce physically valid rearrangement trajectories for a range of 3D object reconfiguration problems without requiring more than an environment description and start and goal arrangements.