273 citations · 356 across the 14 of their papers we have counts for
6 papers · 1 filter
Can AI Perceive Physical Danger and Intervene?
Abhishek Jindal, Dmitry Kalashnikov, R. Alex Hofer +5
When AI interacts with the physical world -- as a robot or an assistive agent -- new safety challenges emerge beyond those of purely ``digital AI". In such interactions, the potent…
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
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…
Generating Robot Constitutions & Benchmarks for Semantic Safety
Pierre Sermanet, Anirudha Majumdar, Alex Irpan +2
Until recently, robotics safety research was predominantly about collision avoidance and hazard reduction in the immediate vicinity of a robot. Since the advent of large vision and…
SciFi-Benchmark: Leveraging Science Fiction To Improve Robot Behavior
Pierre Sermanet, Anirudha Majumdar, Vikas Sindhwani
Given the recent rate of progress in artificial intelligence (AI) and robotics, a tantalizing question is emerging: would robots controlled by emerging AI systems be strongly align…
Predictive Red Teaming: Breaking Policies Without Breaking Robots
Anirudha Majumdar, Mohit Sharma, Dmitry Kalashnikov +3
Visuomotor policies trained via imitation learning are capable of performing challenging manipulation tasks, but are often extremely brittle to lighting, visual distractors, and ob…