Skip to Main content Skip to Navigation

Knowledge representation and exploitation for interactive and cognitive robots

Guillaume Sarthou 1 
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : As robots begin to enter our daily lives, we need advanced knowledge representations and associated reasoning capabilities to enable them to understand and model their environments. Considering the presence of humans in such environments, and therefore the need to interact with them, this need comes with additional requirements. Indeed, knowledge is no longer used by the robot for the sole purpose of being able to act physically on the environment but also to communicate and share information with humans. Therefore knowledge should no longer be understandable only by the robot itself, but should also be able to be narrative-enabled. In the first part of this thesis, we present our first contribution with Ontologenius. This software allows to maintain knowledge bases in the form of ontology, to reason on them and to manage them dynamically. We start by explaining how this software is suitable for \acrfull{hri} applications. To that end, for example to implement theory of mind abilities, it is possible to represent the robot's knowledge base as well as an estimate of the knowledge bases of human partners. We continue with a presentation of its interfaces. This part ends with a performance analysis, demonstrating its online usability. In a second part, we present our contribution to two knowledge exploration problems around the general topic of spatial referring and the use of semantic knowledge. We start with the route description task which aims to propose a set of possible routes leading to a target destination, in the framework of a guiding task. To achieve this task, we propose an ontology allowing us to describe the topology of indoor environments and two algorithms to search for routes. The second knowledge exploration problem we tackle is the \acrfull{reg} problem. It aims at selecting the optimal set of piece of information to communicate in order to allow a hearer to identify the referred entity in a given context. This contribution is then refined to use past activities coming from joint action between a robot and a human, in order to generate new kinds of Referring Expressions. It is also linked with a symbolic task planner to estimate the feasibility and cost of future communications. We conclude this thesis by the presentation of two cognitive architectures. The first one uses the route description contribution and the second one takes advantage of our Referring Expression Generation contribution. Both of them use Ontologenius to manage the semantic Knowledge Base. Through these two architectures, we present how our contributions enable Knowledge Base to gradually take a central role, providing knowledge to all the components of the architectures.
Complete list of metadata
Contributor : ABES STAR :  Contact
Submitted on : Thursday, March 10, 2022 - 2:38:20 PM
Last modification on : Wednesday, June 1, 2022 - 4:40:55 AM


Version validated by the jury (STAR)


  • HAL Id : tel-03404043, version 2


Guillaume Sarthou. Knowledge representation and exploitation for interactive and cognitive robots. Library and information sciences. Université Paul Sabatier - Toulouse III, 2021. English. ⟨NNT : 2021TOU30104⟩. ⟨tel-03404043v2⟩



Record views


Files downloads