Object manipulation planning and replanning for robots with humans

Hisashi Hayashi, Masaru Adachi, Kazuhiko Yokoyama, Hideki Ogawa, Nobuto Matsuhira

Research output: Contribution to journalArticle

Abstract

We introduce new heuristics of HTN (Hierarchical Task Network) planning for mobile robots with two arms/hands that pick and place objects among movable obstacles. Based on our new heuristics, the robot moves obstacles if necessary, picks and places the target objects without collisions. The robot chooses the (right or left) hand to use for each manipulation in order to avoid collisions and reduce the number of obstacle movements. Although we do not use detailed 2D/3D maps and specifications of arms, our heuristics roughly check the collisions. Therefore, we can produce task plans that are executable by lower-level modules. This paper also shows that replanning is effective not only for adapting to human behaviors but also for saving total plan execution time. For example, when a person removes obstacles for the robot, the robot can save time by replanning and omitting this obstacle removal. In another example, suppose that the robot is moving an object to place A, following the user's instruction. If the user changes his/her mind and reinstructs the robot to move the object to another place B, the robot does not have to move the object to A before moving it to B. In these cases, we show that the robot can save much time by task-level replanning.

Original languageEnglish
Pages (from-to)122-130
Number of pages9
JournalTransactions of the Japanese Society for Artificial Intelligence
Volume28
Issue number2
DOIs
Publication statusPublished - 2013

Fingerprint

Robots
Planning
End effectors
Mobile robots
Specifications

Keywords

  • Human-robot interaction
  • Intelligent robotics
  • Manipulation
  • Planning
  • Replanning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Object manipulation planning and replanning for robots with humans. / Hayashi, Hisashi; Adachi, Masaru; Yokoyama, Kazuhiko; Ogawa, Hideki; Matsuhira, Nobuto.

In: Transactions of the Japanese Society for Artificial Intelligence, Vol. 28, No. 2, 2013, p. 122-130.

Research output: Contribution to journalArticle

Hayashi, Hisashi ; Adachi, Masaru ; Yokoyama, Kazuhiko ; Ogawa, Hideki ; Matsuhira, Nobuto. / Object manipulation planning and replanning for robots with humans. In: Transactions of the Japanese Society for Artificial Intelligence. 2013 ; Vol. 28, No. 2. pp. 122-130.
@article{a3fd211827474a5ebf2ad9889e422319,
title = "Object manipulation planning and replanning for robots with humans",
abstract = "We introduce new heuristics of HTN (Hierarchical Task Network) planning for mobile robots with two arms/hands that pick and place objects among movable obstacles. Based on our new heuristics, the robot moves obstacles if necessary, picks and places the target objects without collisions. The robot chooses the (right or left) hand to use for each manipulation in order to avoid collisions and reduce the number of obstacle movements. Although we do not use detailed 2D/3D maps and specifications of arms, our heuristics roughly check the collisions. Therefore, we can produce task plans that are executable by lower-level modules. This paper also shows that replanning is effective not only for adapting to human behaviors but also for saving total plan execution time. For example, when a person removes obstacles for the robot, the robot can save time by replanning and omitting this obstacle removal. In another example, suppose that the robot is moving an object to place A, following the user's instruction. If the user changes his/her mind and reinstructs the robot to move the object to another place B, the robot does not have to move the object to A before moving it to B. In these cases, we show that the robot can save much time by task-level replanning.",
keywords = "Human-robot interaction, Intelligent robotics, Manipulation, Planning, Replanning",
author = "Hisashi Hayashi and Masaru Adachi and Kazuhiko Yokoyama and Hideki Ogawa and Nobuto Matsuhira",
year = "2013",
doi = "10.1527/tjsai.28.122",
language = "English",
volume = "28",
pages = "122--130",
journal = "Transactions of the Japanese Society for Artificial Intelligence",
issn = "1346-0714",
publisher = "Japanese Society for Artificial Intelligence",
number = "2",

}

TY - JOUR

T1 - Object manipulation planning and replanning for robots with humans

AU - Hayashi, Hisashi

AU - Adachi, Masaru

AU - Yokoyama, Kazuhiko

AU - Ogawa, Hideki

AU - Matsuhira, Nobuto

PY - 2013

Y1 - 2013

N2 - We introduce new heuristics of HTN (Hierarchical Task Network) planning for mobile robots with two arms/hands that pick and place objects among movable obstacles. Based on our new heuristics, the robot moves obstacles if necessary, picks and places the target objects without collisions. The robot chooses the (right or left) hand to use for each manipulation in order to avoid collisions and reduce the number of obstacle movements. Although we do not use detailed 2D/3D maps and specifications of arms, our heuristics roughly check the collisions. Therefore, we can produce task plans that are executable by lower-level modules. This paper also shows that replanning is effective not only for adapting to human behaviors but also for saving total plan execution time. For example, when a person removes obstacles for the robot, the robot can save time by replanning and omitting this obstacle removal. In another example, suppose that the robot is moving an object to place A, following the user's instruction. If the user changes his/her mind and reinstructs the robot to move the object to another place B, the robot does not have to move the object to A before moving it to B. In these cases, we show that the robot can save much time by task-level replanning.

AB - We introduce new heuristics of HTN (Hierarchical Task Network) planning for mobile robots with two arms/hands that pick and place objects among movable obstacles. Based on our new heuristics, the robot moves obstacles if necessary, picks and places the target objects without collisions. The robot chooses the (right or left) hand to use for each manipulation in order to avoid collisions and reduce the number of obstacle movements. Although we do not use detailed 2D/3D maps and specifications of arms, our heuristics roughly check the collisions. Therefore, we can produce task plans that are executable by lower-level modules. This paper also shows that replanning is effective not only for adapting to human behaviors but also for saving total plan execution time. For example, when a person removes obstacles for the robot, the robot can save time by replanning and omitting this obstacle removal. In another example, suppose that the robot is moving an object to place A, following the user's instruction. If the user changes his/her mind and reinstructs the robot to move the object to another place B, the robot does not have to move the object to A before moving it to B. In these cases, we show that the robot can save much time by task-level replanning.

KW - Human-robot interaction

KW - Intelligent robotics

KW - Manipulation

KW - Planning

KW - Replanning

UR - http://www.scopus.com/inward/record.url?scp=84946189823&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84946189823&partnerID=8YFLogxK

U2 - 10.1527/tjsai.28.122

DO - 10.1527/tjsai.28.122

M3 - Article

VL - 28

SP - 122

EP - 130

JO - Transactions of the Japanese Society for Artificial Intelligence

JF - Transactions of the Japanese Society for Artificial Intelligence

SN - 1346-0714

IS - 2

ER -