52 citations · 90 across the 11 of their papers we have counts for
13 papers
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…
Real-to-Sim Robot Policy Evaluation with Gaussian Splatting Simulation of Soft-Body Interactions
Kaifeng Zhang, Shuo Sha, Hanxiao Jiang +7
Robotic manipulation policies are advancing rapidly, but their direct evaluation in the real world remains costly, time-consuming, and difficult to reproduce, particularly for task…
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…
HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder
Yingqi Tang, Zhuoran Xu, Zhaotie Meng +1
Although end-to-end autonomous driving (E2E-AD) technologies have made significant progress in recent years, there remains an unsatisfactory performance on closed-loop evaluation.…
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
Bridging the Resource Gap: Deploying Advanced Imitation Learning Models onto Affordable Embedded Platforms
Haizhou Ge, Ruixiang Wang, Zhu-ang Xu +7
Advanced imitation learning with structures like the transformer is increasingly demonstrating its advantages in robotics. However, deploying these large-scale models on embedded p…
Vision Language Models are In-Context Value Learners
Yecheng Jason Ma, Joey Hejna, Ayzaan Wahid +15
Predicting temporal progress from visual trajectories is important for intelligent robots that can learn, adapt, and improve. However, learning such progress estimator, or temporal…
Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs
Hao-Tien Lewis Chiang, Zhuo Xu, Zipeng Fu +19
An elusive goal in navigation research is to build an intelligent agent that can understand multimodal instructions including natural language and image, and perform useful navigat…
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Soroush Nasiriany, Fei Xia, Wenhao Yu +20
Vision language models (VLMs) have shown impressive capabilities across a variety of tasks, from logical reasoning to visual understanding. This opens the door to richer interactio…
Generative Expressive Robot Behaviors using Large Language Models
Karthik Mahadevan, Jonathan Chien, Noah Brown +6
People employ expressive behaviors to effectively communicate and coordinate their actions with others, such as nodding to acknowledge a person glancing at them or saying "excuse m…
SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities
Boyuan Chen, Zhuo Xu, Sean Kirmani +6
Understanding and reasoning about spatial relationships is a fundamental capability for Visual Question Answering (VQA) and robotics. While Vision Language Models (VLM) have demons…
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents
Michael Ahn, Debidatta Dwibedi, Chelsea Finn +24
Foundation models that incorporate language, vision, and more recently actions have revolutionized the ability to harness internet scale data to reason about useful tasks. However,…
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
Jiayuan Gu, Sean Kirmani, Paul Wohlhart +14
Generalization remains one of the most important desiderata for robust robot learning systems. While recently proposed approaches show promise in generalization to novel objects, s…