Publication

Behavior estimation for a complete framework for human motion prediction in crowded environments

Conference Article

Conference

IEEE International Conference on Robotics and Automation (ICRA)

Edition

2014

Pages

5940-5945

Doc link

http://dx.doi.org/10.1109/ICRA.2014.6907734

File

Download the digital copy of the doc pdf document

Abstract

In the present work, we propose and validate a complete probabilistic framework for human motion prediction in urban or social environments. Additionally, we formulate a powerful and useful tool: the human motion behavior estimator. Three different basic behaviors have been detected: Aware, Balanced and Unaware. Our approach is based on the Social Force Model (SFM) and the intentionality prediction BHMIP. The main contribution of the present work is to make use of the behavior estimator for formulating a reliable prediction framework of human trajectories under the influence of dynamic crowds, robots, and in general any moving obstacle. Accordingly, we have demonstrated the great performance of our long-term prediction algorithm, in real scenarios, comparing to other prediction methods.

Categories

service robots.

Scientific reference

G. Ferrer and A. Sanfeliu. Behavior estimation for a complete framework for human motion prediction in crowded environments, 2014 IEEE International Conference on Robotics and Automation, 2014, Hong Kong, pp. 5940-5945.