Rearrangement: A challenge for embodied ai
We describe a framework for research and evaluation in Embodied AI. Our proposal is
based on a canonical task: Rearrangement. A standard task can focus the development of …
based on a canonical task: Rearrangement. A standard task can focus the development of …
Lego-net: Learning regular rearrangements of objects in rooms
Humans universally dislike the task of cleaning up a messy room. If machines were to help
us with this task, they must understand human criteria for regular arrangements, such as …
us with this task, they must understand human criteria for regular arrangements, such as …
Algorithms and systems for manipulating multiple objects
Robot manipulation of multiple objects is an important topic for applications including
warehouse automation, service robots performing cleaning, and large-scale object sorting …
warehouse automation, service robots performing cleaning, and large-scale object sorting …
Online replanning in belief space for partially observable task and motion problems
To solve multi-step manipulation tasks in the real world, an autonomous robot must take
actions to observe its environment and react to unexpected observations. This may require …
actions to observe its environment and react to unexpected observations. This may require …
Nerp: Neural rearrangement planning for unknown objects
Robots will be expected to manipulate a wide variety of objects in complex and arbitrary
ways as they become more widely used in human environments. As such, the …
ways as they become more widely used in human environments. As such, the …
Sg-bot: Object rearrangement via coarse-to-fine robotic imagination on scene graphs
Object rearrangement is pivotal in robotic-environment interactions, representing a
significant capability in embodied AI. In this paper, we present SG-Bot, a novel …
significant capability in embodied AI. In this paper, we present SG-Bot, a novel …
Monte-carlo tree search for efficient visually guided rearrangement planning
We address the problem of visually guided rearrangement planning with many movable
objects, ie, finding a sequence of actions to move a set of objects from an initial arrangement …
objects, ie, finding a sequence of actions to move a set of objects from an initial arrangement …
Randomized physics-based motion planning for grasping in cluttered and uncertain environments
Planning motions to grasp an object in cluttered and uncertain environments is a
challenging task, particularly when a collision-free trajectory does not exist and objects …
challenging task, particularly when a collision-free trajectory does not exist and objects …
End-to-end nonprehensile rearrangement with deep reinforcement learning and simulation-to-reality transfer
Nonprehensile rearrangement is the problem of controlling a robot to interact with objects
through pushing actions in order to reconfigure the objects into a predefined goal pose. In …
through pushing actions in order to reconfigure the objects into a predefined goal pose. In …
Multi-object rearrangement with monte carlo tree search: A case study on planar nonprehensile sorting
In this work, we address a planar non-prehensile sorting task. Here, a robot needs to push
many densely packed objects belonging to different classes into a configuration where these …
many densely packed objects belonging to different classes into a configuration where these …