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Combining Task and Motion Planning is Not Always a Good Idea
Örebro universitet, Institutionen för naturvetenskap och teknik. (AASS)
Örebro universitet, Institutionen för naturvetenskap och teknik. (AASS)ORCID-id: 0000-0002-0458-2146
Örebro universitet, Institutionen för naturvetenskap och teknik. (AASS)
Örebro universitet, Institutionen för naturvetenskap och teknik. (AASS)ORCID-id: 0000-0001-8229-1363
2013 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Combining task and motion planning requires tointerleave causal and geometric reasoning, in order to guaranteethe plan to be executable in the real world. The resulting searchspace, which is the cross product of the symbolic search spaceand the geometric search space, is huge. Systematically calling ageometric reasoner while evaluating symbolic actions is costly. Onthe other hand, geometric reasoning can prune out large parts ofthis search space if geometrically infeasible actions are detectedearly. Hence, we hypothesized the existence of a search depthlevel, until which geometric reasoning can be interleaved withsymbolic reasoning with tractable combinatorial explosion, whilekeeping the benefits of this pruning. In this paper, we propose asimple model that proves the existence of such search depth level,and validate it empirically through experiments in simulation

sted, utgiver, år, opplag, sider
2013.
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Forskningsprogram
Datavetenskap
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URN: urn:nbn:se:oru:diva-30821OAI: oai:DiVA.org:oru-30821DiVA, id: diva2:648554
Konferanse
2013 Robotics: Science and Systems Conference (Workshop "Combined Robot Motion Planning and AI Planning for Practical Applications")
Forskningsfinansiär
EU, FP7, Seventh Framework ProgrammeTilgjengelig fra: 2013-09-16 Laget: 2013-09-16 Sist oppdatert: 2018-01-18bibliografisk kontrollert

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Lagriffoul, FabienKarlsson, LarsBidot, JulienSaffiotti, Alessandro

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