oru.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Geometric backtracking for combined task and path planning in robotic systems
Örebro universitet, Institutionen för naturvetenskap och teknik. (Centre For Applied Autonomous Sensor Systems ( AASS ))
Örebro universitet, Institutionen för naturvetenskap och teknik. (Centre For Applied Autonomous Sensor Systems ( AASS ))ORCID-id: 0000-0002-0458-2146
Örebro universitet, Institutionen för naturvetenskap och teknik. (Centre For Applied Autonomous Sensor Systems ( AASS ))
Örebro universitet, Institutionen för naturvetenskap och teknik. (Centre For Applied Autonomous Sensor Systems ( AASS ))ORCID-id: 0000-0001-8229-1363
(engelsk)Manuskript (preprint) (Annet vitenskapelig)
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. 

Emneord [en]
geometric backtracking, task planning, path planning, robotic systems
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:oru:diva-32778OAI: oai:DiVA.org:oru-32778DiVA, id: diva2:679333
Prosjekter
GeRTSAUNA
Forskningsfinansiär
EU, FP7, Seventh Framework Programme, 248273Knowledge FoundationTilgjengelig fra: 2013-12-14 Laget: 2013-12-14 Sist oppdatert: 2018-01-11bibliografisk kontrollert

Open Access i DiVA

Technical report 1(2130 kB)746 nedlastinger
Filinformasjon
Fil FULLTEXT01.pdfFilstørrelse 2130 kBChecksum SHA-512
c8e8fa114e78d88a1edc4421d012d6c4befe7bd7437c30c4867eb514367050583452aa81b3030ab8b60ded347741f8aef50bc2cbb282c57d23954e4631138b66
Type fulltextMimetype application/pdf

Personposter BETA

Bidot, JulienKarlsson, LarsLagriffoul, FabienSaffiotti, Alessandro

Søk i DiVA

Av forfatter/redaktør
Bidot, JulienKarlsson, LarsLagriffoul, FabienSaffiotti, Alessandro
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar
Totalt: 746 nedlastinger
Antall nedlastinger er summen av alle nedlastinger av alle fulltekster. Det kan for eksempel være tidligere versjoner som er ikke lenger tilgjengelige

urn-nbn

Altmetric

urn-nbn
Totalt: 1492 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf