A Framework for Joint Grasp and Motion Planning in Confined Spaces

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00375956" target="_blank" >RIV/68407700:21230/24:00375956 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/RoMoCo60539.2024.10604306" target="_blank" >https://doi.org/10.1109/RoMoCo60539.2024.10604306</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/RoMoCo60539.2024.10604306" target="_blank" >10.1109/RoMoCo60539.2024.10604306</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Framework for Joint Grasp and Motion Planning in Confined Spaces

Popis výsledku v původním jazyce

Robotic grasping is a fundamental skill across all domains of robot applications. There is a large body of research for grasping objects in table-top scenarios, where finding suitable grasps is the main challenge. In this work, we are interested in scenarios where the objects are in confined spaces and hence particularly difficult to reach. Planning how the robot approaches the object becomes a major part of the challenge, giving rise to methods for joint grasp and motion planning. The framework proposed in this paper provides 20 benchmark scenarios with systematically increasing difficulty, realistic objects with precomputed grasp annotations, and tools to create and share more scenarios. We further provide two baseline planners and evaluate them on the scenarios, demonstrating that the proposed difficulty levels indeed offer a meaningful progression. We invite the research community to build upon this framework by making all components publicly available as open source.

Název v anglickém jazyce

A Framework for Joint Grasp and Motion Planning in Confined Spaces

Popis výsledku anglicky

Robotic grasping is a fundamental skill across all domains of robot applications. There is a large body of research for grasping objects in table-top scenarios, where finding suitable grasps is the main challenge. In this work, we are interested in scenarios where the objects are in confined spaces and hence particularly difficult to reach. Planning how the robot approaches the object becomes a major part of the challenge, giving rise to methods for joint grasp and motion planning. The framework proposed in this paper provides 20 benchmark scenarios with systematically increasing difficulty, realistic objects with precomputed grasp annotations, and tools to create and share more scenarios. We further provide two baseline planners and evaluate them on the scenarios, demonstrating that the proposed difficulty levels indeed offer a meaningful progression. We invite the research community to build upon this framework by making all components publicly available as open source.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2024 13th International Workshop on Robot Motion and Control (RoMoCo)

ISBN

979-8-3503-9397-2

ISSN

2575-5536

e-ISSN

2575-5579

Počet stran výsledku

7

Strana od-do

96-102

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Poznan

Datum konání akce

2. 7. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001285154500005