A dynamic field approach to goal inference and error monitoring for human-robot...

• Author(s): Bicho, E. ; Louro, Luís ; Hipólito, Nzoji ; Erlhagen, Wolfram
• Date: 2009
• Persistent ID: http://hdl.handle.net/1822/10306
• Origin: RepositóriUM - Universidade do Minho
• Subject(s): Human-robot interaction; Goal inference; Error monitoring; Joint action; Anticipatory behavior; Action understanding; Dynamic neural fields
• Document Type: Conference Object
• Language: English

Description

In this paper we present results of our ongoing research on non-verbal human-robot interaction that is heavily inspired by recent experimental findings about the neuro-cognitive mechanisms supporting joint action in humans. The robot control architecture implements the joint coordination of actions and goals as a dynamic process that integrates contextual cues, shared task knowledge and the predicted outcome of the user’s motor behavior. The architecture is formalized by a coupled system of dynamic neural fields representing a distributed network of local but connected neural populations with specific functionalities. We validate the approach in a task in which a robot and a human user jointly construct a toy ’vehicle’. We show that the context-dependent mapping from action observation onto appropriate complementary actions allows the robot to cope with dynamically changing joint action situations. This includes a basic form of error monitoring and compensation.