Pablo Osorio

About

Pablo Osorio is a pioneering researcher at the intersection of human-robot interaction and socially intelligent robotics. His work centers on designing robots that communicate through non-verbal behaviors, fostering emotional bonds between users and machines. Osorio’s most impactful contribution is **Yōkobo** (2022, 16 citations), a “robject” inspired by slow technology that greets people at the entrance and mirrors their interactions to strengthen relationships—such as between couples. He further advanced the field with a **generative model** (2024, 12 citations) that embeds human expressivity into robot motions by combining variational autoencoders and GANs, enabling robots to move with nuanced, human-like emotion. Osorio also developed a **presence robot integrated into smart homes** (2023, 8 citations), using a Raspberry Pi and Bluetooth app to adapt behaviors based on shared data. His recent work on **adaptive contact-rich manipulation** (2024) tackles few-shot imitation learning with force-torque feedback, reducing the need for extensive demonstrations. With a growing citation impact and a focus on making robots emotionally resonant and context-aware, Osorio is shaping a future where machines don’t just assist—they connect.

Research Focus

Key Achievements

Top Papers

1. 1
   Yōkobo: A Robot to Strengthen Links Amongst Users with Non-Verbal Behaviours

   16 citations · 2022
2. 2
   A Generative Model to Embed Human Expressivity into Robot Motions

   12 citations · 2024
3. 3
   Integration of a Presence Robot in a Smart Home

   8 citations · 2023
4. 4
   Adaptive Contact-Rich Manipulation Through Few-Shot Imitation Learning With Force-Torque Feedback and Pre-Trained Object Representations

   3 citations · 2024
5. 5
   Control of a Robot Expressive Movements Using Non-Verbal Features

   3 citations · 2022

Key Collaborators

Contact & Links