Title: DeepMoTIon: Learning to Navigate Like Humans,
Abstract: We present a novel human-aware navigation approach, where the robot learns to
mimic humans to navigate safely in crowds. The presented model referred to as
DeepMoTIon, is trained with pedestrian surveillance data to predict human
velocity. The robot processes LiDAR scans via the trained network to navigate
to the target location. We conduct extensive experiments to assess the
different components of our network and prove the necessity of each to imitate
humans. Our experiments show that DeepMoTIon outperforms state-of-the-art in
terms of human imitation and reaches the target on 100% of the test cases
without breaching humans' safe distance.