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
Authors
Projects associated
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, China, pp. 5940-5945.
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