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Article: Reactive motion planning using time-layered C-spaces for a collaborative robot PaDY

TitleReactive motion planning using time-layered C-spaces for a collaborative robot PaDY
Authors
KeywordsHuman–robot collaboration
Collision avoidance
Sampling-based path planning
Issue Date2021
Citation
Advanced Robotics, 2021, v. 35, n. 8, p. 490-503 How to Cite?
AbstractA reactive motion-planning for collaborative robots using the time-layered C-spaces (TLC-spaces) is proposed in this paper. First, the time-augmented C-space (TAC-space) is introduced. TAC-space is an implementation of the configuration-time space with multiple moving obstacles [Latombe JC. Robot motion planning. Kluwer Academic; 1991. p. 22, 23]. The TAC-space is obtained by stacking the current and predicted future C-spaces along the time axis using predicted motions of the obstacles. Then, TLC-spaces is constructed as the collection of only those C-spaces in the TAC-space that are relevant to the motion planning with moving obstacles. The trajectory that reaches the goal configuration at the specified target time is generated under dynamic constraints including robot velocity and acceleration. We focus on a collaborative robot, PaDY, whose task is to deliver tools and parts to the worker in a factory. Similar to an actual assembly process in an automobile production system, six scenarios are selected for the evaluation of the proposed motion planning method. The simulation results using the real-life motion of workers show that the computation time required for the proposed motion planning using TLC-spaces is shorter than that of our previous method using TAC-space. The experimental results show that the proposed method is applicable to PaDY in human environments.
Persistent Identifierhttp://hdl.handle.net/10722/303025
ISSN
2021 Impact Factor: 2.057
2020 SCImago Journal Rankings: 0.466
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWada, Hisaka-
dc.contributor.authorKinugawa, Jun-
dc.contributor.authorKosuge, Kazuhiro-
dc.date.accessioned2021-09-07T08:43:03Z-
dc.date.available2021-09-07T08:43:03Z-
dc.date.issued2021-
dc.identifier.citationAdvanced Robotics, 2021, v. 35, n. 8, p. 490-503-
dc.identifier.issn0169-1864-
dc.identifier.urihttp://hdl.handle.net/10722/303025-
dc.description.abstractA reactive motion-planning for collaborative robots using the time-layered C-spaces (TLC-spaces) is proposed in this paper. First, the time-augmented C-space (TAC-space) is introduced. TAC-space is an implementation of the configuration-time space with multiple moving obstacles [Latombe JC. Robot motion planning. Kluwer Academic; 1991. p. 22, 23]. The TAC-space is obtained by stacking the current and predicted future C-spaces along the time axis using predicted motions of the obstacles. Then, TLC-spaces is constructed as the collection of only those C-spaces in the TAC-space that are relevant to the motion planning with moving obstacles. The trajectory that reaches the goal configuration at the specified target time is generated under dynamic constraints including robot velocity and acceleration. We focus on a collaborative robot, PaDY, whose task is to deliver tools and parts to the worker in a factory. Similar to an actual assembly process in an automobile production system, six scenarios are selected for the evaluation of the proposed motion planning method. The simulation results using the real-life motion of workers show that the computation time required for the proposed motion planning using TLC-spaces is shorter than that of our previous method using TAC-space. The experimental results show that the proposed method is applicable to PaDY in human environments.-
dc.languageeng-
dc.relation.ispartofAdvanced Robotics-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectHuman–robot collaboration-
dc.subjectCollision avoidance-
dc.subjectSampling-based path planning-
dc.titleReactive motion planning using time-layered C-spaces for a collaborative robot PaDY-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1080/01691864.2021.1896381-
dc.identifier.scopuseid_2-s2.0-85102438919-
dc.identifier.volume35-
dc.identifier.issue8-
dc.identifier.spage490-
dc.identifier.epage503-
dc.identifier.eissn1568-5535-
dc.identifier.isiWOS:000627285700001-

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