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Geometric backtracking for combined task and path planning in robotic systems
Örebro University, School of Science and Technology, Örebro University, Sweden. (Centre For Applied Autonomous Sensor Systems ( AASS ))
Örebro University, School of Science and Technology, Örebro University, Sweden. (Centre For Applied Autonomous Sensor Systems ( AASS ))ORCID iD: 0000-0002-0458-2146
Örebro University, School of Science and Technology, Örebro University, Sweden. (Centre For Applied Autonomous Sensor Systems ( AASS ))
Örebro University, School of Science and Technology, Örebro University, Sweden. (Centre For Applied Autonomous Sensor Systems ( AASS ))ORCID iD: 0000-0001-8229-1363
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Planners for real, possibly complex, robotic systems should not only reason about abstract actions, but also about aspects related to physical execution such as kinematics and geometry. We present an approach in which state-based forward-chaining task planning is tightly coupled with sampling-based motion planning and other forms of geometric reasoning. We focus on the problem of geometric backtracking which arises when a planner needs to reconsider geometric choices, like grasps and poses, that were made for previous actions, in order to satisfy geometric preconditions of the current action. Geometric backtracking is a necessary condition for completeness, but it may lead to a dramatic computational explosion due to the systematic exploration of the space of geometric states. In order to deal with that, we introduce heuristics based on the collisions between the robot and movable objects detected during geometric backtracking and on kinematic relations between actions. We also present a complementary approach based on propagating explicit constraints which are automatically generated from the symbolic actions to be evaluated and from the kinematic model of the robot. We empirically evaluate these dierent approaches. We demonstrate our planner on a real advanced robot, the DLR Justin robot, and on a simulated autonomous forklift. 

Keyword [en]
geometric backtracking, task planning, path planning, robotic systems
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-32778OAI: oai:DiVA.org:oru-32778DiVA: diva2:679333
Projects
GeRTSAUNA
Funder
EU, FP7, Seventh Framework Programme, 248273Knowledge Foundation
Available from: 2013-12-14 Created: 2013-12-14 Last updated: 2016-08-10Bibliographically approved

Open Access in DiVA

Technical report 1(2130 kB)316 downloads
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Bidot, JulienKarlsson, LarsLagriffoul, FabienSaffiotti, Alessandro
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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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