Papers
5
Total Citations
53
H-Index
4
About
Hailong Liu is a researcher whose work spans developmental robotics, human-robot interaction, and autonomous vehicle systems. His key research areas include unsupervised word discovery from speech signals, pedestrian-autonomous vehicle interaction, underwater robotics, and human-machine interfaces for semi-autonomous vehicles. Liu’s most cited work, “Double articulation analyzer with deep sparse autoencoder for unsupervised word discovery from speech signals” (2016, 29 citations), addresses the challenge of enabling robots to directly discover words from audio signals, mimicking human infants’ developmental capabilities. He has also contributed to understanding pedestrian gaze behavior during interactions with automated vehicles (2020, 8 citations), highlighting trust issues when vehicle intentions are unclear. His work on cooperative path-following control for remotely operated underwater vehicles (2022, 8 citations) aims to reduce operator workload during inspection tasks. More recently, Liu has explored robotic in-car accessories for semi-autonomous vehicles (2024, 5 citations) to enhance driver trust during handover. His research demonstrates a commitment to bridging developmental robotics with practical applications in autonomous systems, underwater robotics, and human-robot interaction, with a focus on improving safety, trust, and efficiency in human-machine collaborations.
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