VICA: A Vicarious Cognitive Architecture Environment Model for Navigation Among Movable Obstacles

Abstract

: This article presents a new Cognitive Architecture Environment model for Navigation Among Movable Obstacles (NAMO). This model is the result of a novel approach based on the Theory of Mind and more particularly on the notion of ’vicariance’ as an essential strategy of the robot’s interaction with outside world. The implementation of our model follows the advances in AI and the Cognitive Robotics research area, where a cognitive architecture environment is represented as a Multi-Agent System (MAS). The MAS representation offers the robot the ability to produce a representation of its environment as well as the possibility to run all types of action simulations in order to anticipate the environment’s reactions. The environment state values, both predictive and real as transcribed during simulation and real action movements, are compared to each other in order to keep the correct ones and avoid errors. This is a continuous learning and leads to the construction of a safe path of actions into a dynamic environment. The experiment results show the efficiency of our model, offering an intelligent guide to the robot in order to perform tasks among mobile agents, by avoiding a maximum number of obstacles.