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of human body models (HBM) able to predict human motion and postural control (both anticipatory as preparation for upcoming perturbation, and compensatory for restoring balance after perturbation). To model
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such as vehicle cabins present a lot of clutter and multipath masking the signature of the person or people to observe; and 2) the human body is a rather complicated object to observe with radar, as we want
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Challenge: Reliable and affordable sensing for driving automation. Change: Synergy between human drivers & vehicular sensing systems. Impact: Automated vehicles that can handle safety-critical
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adapt to the patient. You will thus pave the way to next-generation small- to large-scale neuromorphic architectures inspired by the human neocortex, targeting low-footprint adaptive devices such as
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of seamless interaction in human populated environments, primarily due to the high complexity of modeling and reasoning over the effect that robot actions have on other robots and humans, and the
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Do you posess expertise in statistical methods and techniques, sociology, mathematics, or the social sciences, coupled with a keen interest in digital technologies and human rights? The Faculty
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The research programme DeepNL aims to improve the fundamental understanding of the dynamics of the deep subsurface under the influence of human interventions and the resulting effects
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of human body models (HBM) able to predict human motion and postural control (both anticipatory as preparation for upcoming perturbation, and compensatory for restoring balance after perturbation). To model
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realistic simulations of human movement? Are you fascinated by how humans adapt their movements as they age? If so, the department of Biomechanics at TU Delft wants you to help us develop the next generation
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Challenge: Human Behavior Recognition and Generation with Large Contextural Behavior Model Change: Incorporate context for human behavior recogintion and generation Impact: Advanced techniques