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Current practices in knowledge representation for robotics

General

  • Name of the project
  • Names of the main contributors

Knowledge model

  • Main paradigms (like ontologies, fluents, semantic frames, relational databases...)
  • How would be represented the fact: "The bottle (id 1845) is on the table (id 2365)"?
  • Which formalisms/standards/standard corpus are used (OWL, FrameNet, Cyc...)
  • Expressivity (for Description Logics, cf http://www.cs.man.ac.uk/~ezolin/dl/)
  • Open World Assumption or Closed World Assumption?
  • Resonning capabilities
    • Reasonner available?
    • If yes, external tool or part of the KB?
  • Capable of representing uncertain knowledge?
  • Management of time?
    • How time is represented?
    • How is it associated to statements?
    • What is it used for?
  • Has an associated rule language?
  • Modifiable at run-time?
    • A-Box only?
    • or T-Box and A-Box?

Area of use

  • Task planning
  • Plan representation
  • Spatial mapping
  • Dialogue grounding
  • Learning/Experience modelling
  • Human-robot interaction
  • Other area?
  • References to main experiment conducted with the KB

Features

  • Capable of fetching external sources of knowledge (like Wikipedia,...)
    • Automaticaly?
  • Grounding mechanism?
    • Could you briefly describe how perception are grounded in the KB?
  • Integration with supervision processes?
    • Could you briefly give an example?
  • Other features?

Other

  • Main programming language
  • How does the KB integrate into the robotic architecture? (language bindings, middleware wrappers...)
  • Has been deployed on a real, physical platform?
    • If yes, has been deployed on more that one platform?
  • Project homepage, API documentation, tutorials/examples
  • Main publications that present the project