Explicit Knowledge and the Deliberative Layer: Lessons Learned
Overview & Synopsis
Over the last four years, we have been slowly ramping up explicit knowledge representation and manipulation in the deliberative and executive layers of our robots. Ranging from situation assessment to symbolic task planning, from verbal interaction to event-driven execution control, we have built up a knowledge-oriented architecture which is now used on a daily basis on our robots. This article presents our design choices, the articulations between the diverse deliberative components of the robot, and the strengths and weaknesses of this approach. We show that explicit knowledge management is not only a convenient tool from the software engineering point of view, but also pushes for a different, more semantic way to address the decision-making issue in autonomous robots.
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Document Information
| Document Title | Explicit Knowledge and the Deliberative Layer: Lessons Learned |
|---|---|
| Author / Organization | Séverin Lemaignan, Rachid Alami |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2013 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-118149 |
| Original Source Link | Visit Source Page on hal.science » |