Primitive Action Recognition based on Semantic Facts - Méthodes et Ingénierie des Langues, des Ontologies et du Discours
Communication Dans Un Congrès Année : 2023

Primitive Action Recognition based on Semantic Facts

Résumé

To interact with humans, a robot has to know actions done by each agent presents in the environment, robotic or not. Robots are not omniscient and can't perceive every actions made but, as humans do, we can equip the robot with the ability to infer what happens from the perceived effects of these actions on the environment. In this paper, we present a lightweight and open-source framework to recognise primitive actions and their parameters. Based on a semantic abstraction of changes in the environment, it allows to recognise unperceived actions. In addition, thanks to its integration into a cognitive robotic architecture implementing perspective-taking and theory of mind, the presented framework is able to estimate the actions recognised by the agent interacting with the robot. These recognition processes are refined on the fly based on the current observations. Tests on real robots demonstrate the framework's usability in interactive contexts.
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Dates et versions

hal-04397039 , version 1 (16-01-2024)

Identifiants

Citer

Adrien Vigné, Guillaume Sarthou, Aurélie Clodic. Primitive Action Recognition based on Semantic Facts. ICSR 2023 - International Conference on Social Robotics, Dec 2023, Doha, Qatar. pp.350--362, ⟨10.1007/978-981-99-8715-3_29⟩. ⟨hal-04397039⟩
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