Papers
7
Total Citations
74
H-Index
5
About
Javier Laplaza is a robotics researcher whose work sits at the intersection of social human-robot interaction, deep learning, and human motion prediction. He is perhaps best known for co-developing IVO, a social robot platform specifically engineered for long-term collaborative human-robot interaction, which has already garnered 20 citations since its 2022 introduction and established a concrete testbed for the field. Much of Laplaza's most influential research focuses on anticipating human intent and movement to make robots safer and more intuitive collaborators. His series of attention-based deep learning models for 3D human motion prediction — particularly applied to handover tasks — demonstrates a consistent effort to incorporate contextual cues such as robot end-effector position, interaction phases, and classified human intention, collectively accumulating nearly 45 citations across multiple publications. His 2024 work on contextual motion prediction and intention inference further extends these contributions, reflecting growing recognition from the research community. Beyond prediction, Laplaza has advanced natural human-robot communication through gesture-based control systems, proposing body language as an intuitive interaction modality backed by custom neural network architectures and purpose-built datasets. Together, his body of work reflects a coherent vision: building robots that don't merely respond to humans, but genuinely understand and anticipate them.
Research Focus
Key Achievements
Top Papers
- 1IVO Robot: A New Social Robot for Human-Robot Collaboration20 citations · 2022
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- 6Body Gesture Recognition to Control a Social Mobile Robot5 citations · 2023
- 7Body Gesture Recognition to Control a Social Robot4 citations · 2022