Prehensile object rearrangement in cluttered and confined spaces has broad applications
but is also challenging. For instance, rearranging products in a grocery shelf means that the …

For rearranging objects on tabletops with overhand grasps, temporarily relocating objects to
some buffer space may be necessary. This raises the natural question of how many …

We investigate the problem of coordinating two robot arms to solve non-monotone tabletop
multi-object re-arrangement tasks. In a non-monotone rearrangement task, complex object …

Robotic systems often face challenges when attempting to grasp a target object due to
interference from surrounding items. We propose a Deep Reinforcement Learning (DRL) …

Effectively rearranging heterogeneous objects constitutes a high-utility skill that an intelligent
robot should master. Whereas significant work has been devoted to the grasp synthesis of …

Real-world manipulation problems in heavy clutter require robots to reason about potential
contacts with objects in the environment. We focus on pick-and-place style tasks to retrieve a …

We investigate the utility of employing multiple buffers in solving a class of rearrangement
problems with pick-n-swap manipulation primitives. In this problem, objects stored randomly …

We are interested in pick-and-place style robot manipulation tasks in cluttered and confined
3D workspaces among movable objects that may be rearranged by the robot and may slide …

Effectively performing object rearrangement is an essential skill for mobile manipulators, eg,
setting up a dinner table or organizing a desk. A key challenge in such problems is deciding …

Scene Rearrangement Planning (SRP) has recently emerged as a crucial interior scene
task; however, current approaches still face two primary issues. First, prior works define the …