Peña, Pedro A.Visser, Ubbo2021-04-232021-04-2320202020http://dx.doi.org/10.1007/s13218-020-00658-7https://dl.gi.de/handle/20.500.12116/36289Tracking and predicting humans in three dimensional space in order to know the location and heading of the human in the environment is a difficult task. Though if solved it will allow a robotic agent to know where it can safely be and navigate the environment without imposing any danger to the human that it is interacting with. We propose a novel probabilistic framework for robotic systems in which multiple models can be fused into a circular probabilitymap to forecast human poses. We developed and implemented the framework and tested it on Toyota’s HSR robot and Waymo Open Dataset. Our experiments show promising results.Text/Journal Article10.1007/s13218-020-00658-71610-1987