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Current practices in knowledge representation for robotics
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General
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- Name of the project
- Names of the main contributors

Knowledge model
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- 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
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- 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
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- 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
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- 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

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