An Online Fuzzy-Based Approach for Human Emotions Detection: An Overview on the Human Cognitive Model of Understanding and Generating Multimodal Actions

Amir Aly (1) , Adriana Tapus (2)

1 RV - Robotique et Vision
2 U2IS - Unité d'Informatique et d'Ingénierie des Systèmes

An intelligent robot needs to be able to understand human emotions, and to understand and generate actions through cognitive systems that operate in a similar way to human cognition. In this chapter, we mainly focus on developing an online incremental learning system of emotions using Takagi-Sugeno (TS) fuzzy model. Additionally, we present a general overview for understanding and generating multimodal actions from the cognitive point of view. The main objective of this system is to detect whether the observed emotion needs a new corresponding multi-modal action to be generated in case it constitutes a new emotion cluster not learnt before, or it can be attributed to one of the existing actions in memory in case it belongs to an existing cluster.

Mots clés: Plutchik model; Takagi-Sugeno (TS) fuzzy model; Poten-tial calculation; Cluster centers

Domaines: Informatique [cs]

Amir Aly, Adriana Tapus. An Online Fuzzy-Based Approach for Human Emotions Detection: An Overview on the Human Cognitive Model of Understanding and Generating Multimodal Actions. S. Mohammed and J.C. Moreno and K. Kong and Y. Amirat. Intelligent Assistive Robots: Recent Advances in Assistive Robotics for Everyday Activities, 106, Springer International Publishing, pp.185-212, 2015, Springer Tracts in Advanced Robotics (STAR), ⟨10.1007/978-3-319-12922-8_7⟩. ⟨hal-01157390⟩