16 citations · 46 across the 12 of their papers we have counts for
12 papers
AEGIS: A Backup Reflex for Physical AI
Josef Chen
Long-horizon robot manipulation tends to fail gradually: one bad step degrades the state, and the policy spirals into a basin from which it cannot recover. The failure is often vis…
AURA: Action-Gated Memory for Robot Policies at Constant VRAM
Josef Chen
The KV-cache is the right memory for datacenters but the wrong memory for robots. Datacenter inference batches many short requests and resets them, amortizing an attention cache ac…
Memory-Bound but Not Bandwidth-Limited: The Physical AI Inference Gap in Batch-1 LLM Decode
Josef Chen
Physical AI systems, including robots, autonomous vehicles, embodied agents and edge copilots, often run a different inference workload from cloud LLM serving: single-stream, batch…
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…
ExoStart: Efficient learning for dexterous manipulation with sensorized exoskeleton demonstrations
Zilin Si, Jose Enrique Chen, M. Emre Karagozler +15
Recent advancements in teleoperation systems have enabled high-quality data collection for robotic manipulators, showing impressive results in learning manipulation at scale. This…
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…
Proc4Gem: Foundation models for physical agency through procedural generation
Yixin Lin, Jan Humplik, Sandy H. Huang +18
In robot learning, it is common to either ignore the environment semantics, focusing on tasks like whole-body control which only require reasoning about robot-environment contacts,…
DemoStart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots
Maria Bauza, Jose Enrique Chen, Valentin Dalibard +13
We present DemoStart, a novel auto-curriculum reinforcement learning method capable of learning complex manipulation behaviors on an arm equipped with a three-fingered robotic hand…
Replay across Experiments: A Natural Extension of Off-Policy RL
Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen +9
Replaying data is a principal mechanism underlying the stability and data efficiency of off-policy reinforcement learning (RL). We present an effective yet simple framework to exte…
RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao +36
The ability to leverage heterogeneous robotic experience from different robots and tasks to quickly master novel skills and embodiments has the potential to transform robot learnin…
Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Ken Caluwaerts, Atil Iscen, J. Chase Kew +41
Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biol…
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes
Alex X. Lee, Coline Devin, Yuxiang Zhou +18
We study the problem of robotic stacking with objects of complex geometry. We propose a challenging and diverse set of such objects that was carefully designed to require strategie…