Generalized spatial behavior cognition model and its applications for intelligent robots

Human behaviors are highly affected by implicit human factors such as culture, social conventions, laws and even the mental states of individuals and groups. If robots are to be accepted by humans, they must conform to common social norms and local customs and recognize highly socialized spatial behaviors. This paper aims to extend the Spatial Behavior Cognition Model (SBCM) proposed in [14] by adding the pedestrian velocity as one of the estimated features of SBCM. In this case, robots can understand more spatial behaviors represented mainly on pedestrian velocity. Experiments for several scenarios of human environments are conducted. The results show that the proposed approach enables robots to accumulate the knowledge needed to ensure good behavior in social situations.