Classification and prediction of human behaviors by a mobile robot

Abstract

Robots interacting and collaborating with people need to comprehend and predict their movements. We present an approach to perceiving and modeling behaviors using a 3D virtual world. The robot’s visual data is registered with the virtual world to construct a model of the dynamics of the behavior and to predict future motions using a physics engine. This enables the robot to visualize alternative evolutions of the dynamics and to classify them. The goal of this work is to use this ability to interact more naturally with humans and to avoid potentially disastrous mistakes.