To Örebro University

oru.seÖrebro University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Object placement planning and optimization for robot manipulators
KTH Royal Institute of Technology, Stockholm, Sweden.
Yale University, New Haven, USA.
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0003-3958-6179
KTH Royal Institute of Technology, Stockholm, Sweden.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

We address the problem of motion planning for a robotic manipulator with the task to place a grasped object in a cluttered environment. In this task, we need to locate a collision-free pose for the object that a) facilitates the stable placement of the object, b) is reachable by the robot manipulator and c) optimizes a user-given placement objective. Because of the placement objective, this problem is more challenging than classical motion planning where the target pose is defined from the start. To solve this task, we propose an anytime algorithm that integrates sampling-based motion planning for the robot manipulator with a novel hierarchical search for suitable placement poses. We evaluate our approach on a dual-arm robot for two different placement objectives, and observe its effectiveness even in challenging scenarios.

National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-78673OAI: oai:DiVA.org:oru-78673DiVA, id: diva2:1379382
Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2019-12-17Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Object Placement Planning and Optimization for Robot Manipulators

Authority records

Stork, Johannes Andreas

Search in DiVA

By author/editor
Stork, Johannes Andreas
By organisation
School of Science and Technology
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 151 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf