EgoTraj is a new open multimodal dataset of 75 long-horizon egocentric human navigation sequences in urban environments with head pose, gaze, and scene data, plus benchmarks of trajectory prediction methods.
arXiv preprint arXiv:2412.00396 (2024)
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Raw proximity measurements can substitute for explicit object localization in humanoid collision avoidance if sensing range is sufficient, and sparse non-directional proximity signals train more efficiently than dense directional alternatives.
Hybrid ToF and self-capacitance sensing combined with soft materials enables multi-modal tactile and proximity detection on 3D-printed robot skins.
citing papers explorer
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EgoTraj: Real-World Egocentric Human Trajectory Dataset for Multimodal Prediction
EgoTraj is a new open multimodal dataset of 75 long-horizon egocentric human navigation sequences in urban environments with head pose, gaze, and scene data, plus benchmarks of trajectory prediction methods.
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Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance
Raw proximity measurements can substitute for explicit object localization in humanoid collision avoidance if sensing range is sufficient, and sparse non-directional proximity signals train more efficiently than dense directional alternatives.
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Improving Sensing Coverage and Compliance of 3D-Printed Artificial Skins Through Multi-Modal Sensing and Soft Materials
Hybrid ToF and self-capacitance sensing combined with soft materials enables multi-modal tactile and proximity detection on 3D-printed robot skins.