Szymon Rusinkiewicz
Papers
8
Total Citations
365
H-Index
5
About
Szymon Rusinkiewicz is a leading researcher in robotics and human-robot interaction, with a focus on personalized assistance and mobile manipulation. His most influential work, **TidyBot**, leverages large language models to enable robots to learn and generalize user preferences for household cleanup, amassing over 189 citations since 2023. This breakthrough demonstrates how robots can personalize physical assistance by reapplying learned behaviors to new scenarios, addressing a key challenge in domestic robotics. Rusinkiewicz also pioneered **Spatial Action Maps** for mobile manipulation, a novel approach that replaces traditional end-to-end navigation with spatially-aware action predictions, significantly improving robot efficiency in cluttered environments. His work on **Spatial Intention Maps** extends this to multi-agent coordination, enabling decentralized robots to collaborate on physical tasks. More recently, he has explored non-prehensile manipulation using pneumatic blowers and applied imitation learning to construction automation, including rebar cage assembly. With over 370 total citations, Rusinkiewicz’s contributions bridge AI, robotics, and practical deployment, making him a notable figure in advancing autonomous systems for real-world assistance.
Research Focus
Key Achievements
Top Papers
- 1TidyBot: personalized robot assistance with large language models189 citations · 2023
- 2Spatial Action Maps for Mobile Manipulation75 citations · 2020
- 3TidyBot: Personalized Robot Assistance with Large Language Models75 citations · 2023
- 4Learning Pneumatic Non-Prehensile Manipulation With a Mobile Blower10 citations · 2022
- 5TidyBot: Personalized Robot Assistance with Large Language Models9 citations · 2023
- 6Spatial Intention Maps for Multi-Agent Mobile Manipulation3 citations · 2021
- 7Mobile robotic rebar cage assembly via imitation learning2 citations · 2025
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