Brainstorming Fuzzy Cognitive Maps for Camera-Based Assistive Navigation

Abstract

Motivated by the brainstorming process of human beings, a novel learning Fuzzy Cognitive Map (FCM) model named Brainstorming Fuzzy Cognitive Map (BFCM) is proposed. The proposed model is based on a state-of-the-art optimization algorithm, named Determinative Brain Storm Optimization, which is utilized to automatically adapt the weights of the FCM structure. In this study, BFCM is applied for safe outdoor navigation of visually impaired individuals. This application ensures the avoidance of static obstacles in an unknown environment, by taking into consideration the output of an obstacle detection system based on a depth camera. The simulation results show that the proposed model can effectively assist the users to avoid static obstacles and safely reach a desired destination, and they promise a wider applicability of the model to other domains, such as robotics.