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Explicit Knowledge and the Deliberative Layer: Lessons Learned

Séverin Lemaignan 1 Rachid Alami 1
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : 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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Submitted on : Saturday, January 12, 2019 - 6:35:02 PM
Last modification on : Thursday, June 10, 2021 - 3:06:32 AM
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  • HAL Id : hal-01979215, version 1


Séverin Lemaignan, Rachid Alami. Explicit Knowledge and the Deliberative Layer: Lessons Learned. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2013, Tokyo, Japan. ⟨hal-01979215⟩



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