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Symbolic and Geometric Planning for teams of Robots and Humans

Raphaël Lallement 1
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : Hierarchical Task Network (HTN) planning is a popular approach to build task plans to control intelligent systems. This thesis presents the HATP (Hierarchical Agent-based Task Planner) planning framework which extends the traditional HTN planning domain representation and semantics by making them more suitable for roboticists, and by offering human-awareness capabilities. When computing human-aware robot plans, it appears that the problems are very complex and highly intricate. To deal with this complexity we have integrated a geometric planner to reason about the actual impact of actions on the environment and allow to take into account the affordances (reachability, visibility). This thesis presents in detail this integration between two heterogeneous planning layers and explores how they can be combined to solve new classes of robotic planning problems
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Submitted on : Wednesday, June 7, 2017 - 3:06:21 PM
Last modification on : Thursday, June 10, 2021 - 3:06:37 AM
Long-term archiving on: : Friday, September 8, 2017 - 12:48:47 PM


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  • HAL Id : tel-01534323, version 1


Raphaël Lallement. Symbolic and Geometric Planning for teams of Robots and Humans. Artificial Intelligence [cs.AI]. INSA de Toulouse, 2016. English. ⟨NNT : 2016ISAT0010⟩. ⟨tel-01534323⟩



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