collaborators

6 papers

cs.RO2026

What Matters in Orchestrating Robot Policies: A Systematic Study of Hierarchical VLA Agents

Jiaheng Hu, Mohit Shridhar, Caden Lu +4

Hierarchical vision-language-action (Hi-VLA) systems have emerged as a promising paradigm for complex robot manipulation, by using high-level VLM planners to decompose tasks into l…

cs.RO2025

Few-Shot Inference of Human Perceptions of Robot Performance in Social Navigation Scenarios

Qiping Zhang, Nathan Tsoi, Mofeed Nagib +2

Understanding how humans evaluate robot behavior during human-robot interactions is crucial for developing socially aware robots that behave according to human expectations. While…

cs.RO2025

Predicting Human Perceptions of Robot Performance During Navigation Tasks

Qiping Zhang, Nathan Tsoi, Mofeed Nagib +4

Understanding human perceptions of robot performance is crucial for designing socially intelligent robots that can adapt to human expectations. Current approaches often rely on sur…

cs.RO2025

Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer

Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169

General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…

cs.RO2025

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie +115

Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as…

cs.RO2025

Feature Aggregation with Latent Generative Replay for Federated Continual Learning of Socially Appropriate Robot Behaviours

Nikhil Churamani, Saksham Checker, Fethiye Irmak Dogan +2

It is critical for robots to explore Federated Learning (FL) settings where several robots, deployed in parallel, can learn independently while also sharing their learning with eac…