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Primitive Action Based Combined Task and Motion Planning for the Service Robot
The need for combined task and motion planning (CTAMP) in robotics is well known as robotic technologies become more mature. The goal of CTAMP is to determine a proper sequence of a robot’s actions based on symbolic and geometric reasoning. Because of the fundamental difference in symbolic and geome...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866450/ https://www.ncbi.nlm.nih.gov/pubmed/35224001 http://dx.doi.org/10.3389/frobt.2022.713470 |
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author | Jeon, Jeongmin Jung, Hong-ryul Yumbla, Francisco Luong, Tuan Anh Moon, Hyungpil |
author_facet | Jeon, Jeongmin Jung, Hong-ryul Yumbla, Francisco Luong, Tuan Anh Moon, Hyungpil |
author_sort | Jeon, Jeongmin |
collection | PubMed |
description | The need for combined task and motion planning (CTAMP) in robotics is well known as robotic technologies become more mature. The goal of CTAMP is to determine a proper sequence of a robot’s actions based on symbolic and geometric reasoning. Because of the fundamental difference in symbolic and geometric reasoning, a CTAMP system often requires an interface module between the two reasoning modules. We propose a CTAMP system in which a symbolic action sequence is generated in task planning, and each action is verified geometrically in motion planning using the off-the-shelf planners and reasoners. The approach is that a set of action models is defined with PDDL in the interface module (action library) and the required information to each planner is automatically provided by the interface module. The proposed method was successfully implemented in three simulated experiments that involve manipulation tasks. According to our findings, the proposed method is effective in responding to changes in the environment and uncertainty with errors in recognition of the environment and the robot motion control. |
format | Online Article Text |
id | pubmed-8866450 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88664502022-02-25 Primitive Action Based Combined Task and Motion Planning for the Service Robot Jeon, Jeongmin Jung, Hong-ryul Yumbla, Francisco Luong, Tuan Anh Moon, Hyungpil Front Robot AI Robotics and AI The need for combined task and motion planning (CTAMP) in robotics is well known as robotic technologies become more mature. The goal of CTAMP is to determine a proper sequence of a robot’s actions based on symbolic and geometric reasoning. Because of the fundamental difference in symbolic and geometric reasoning, a CTAMP system often requires an interface module between the two reasoning modules. We propose a CTAMP system in which a symbolic action sequence is generated in task planning, and each action is verified geometrically in motion planning using the off-the-shelf planners and reasoners. The approach is that a set of action models is defined with PDDL in the interface module (action library) and the required information to each planner is automatically provided by the interface module. The proposed method was successfully implemented in three simulated experiments that involve manipulation tasks. According to our findings, the proposed method is effective in responding to changes in the environment and uncertainty with errors in recognition of the environment and the robot motion control. Frontiers Media S.A. 2022-02-10 /pmc/articles/PMC8866450/ /pubmed/35224001 http://dx.doi.org/10.3389/frobt.2022.713470 Text en Copyright © 2022 Jeon, Jung, Yumbla, Luong and Moon. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Jeon, Jeongmin Jung, Hong-ryul Yumbla, Francisco Luong, Tuan Anh Moon, Hyungpil Primitive Action Based Combined Task and Motion Planning for the Service Robot |
title | Primitive Action Based Combined Task and Motion Planning for the Service Robot |
title_full | Primitive Action Based Combined Task and Motion Planning for the Service Robot |
title_fullStr | Primitive Action Based Combined Task and Motion Planning for the Service Robot |
title_full_unstemmed | Primitive Action Based Combined Task and Motion Planning for the Service Robot |
title_short | Primitive Action Based Combined Task and Motion Planning for the Service Robot |
title_sort | primitive action based combined task and motion planning for the service robot |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866450/ https://www.ncbi.nlm.nih.gov/pubmed/35224001 http://dx.doi.org/10.3389/frobt.2022.713470 |
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