23 papers
Training and Evaluating Diffusion Policies with Long Context Lengths
Abhinav Agarwal, Adam Wei, Taylan Kargin +6
Imitation learning has enabled highly-dexterous robotic manipulation from RGB observations. Policies trained with these methods, however, typically condition robot actions on only…
Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics
Adam Wei, Nicholas Pfaff, Thomas Cohn +4
We propose Ambient Diffusion Policy, a simple and principled method for imitation learning from suboptimal data in robotics. High-quality, task-specific robot data is expensive and…
SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes
Nicholas Pfaff, Thomas Cohn, Sergey Zakharov +2
Simulation has become a key tool for training and evaluating home robots at scale, yet existing environments fail to capture the diversity and physical complexity of real indoor sp…
Large Video Planner Enables Generalizable Robot Control
Boyuan Chen, Tianyuan Zhang, Haoran Geng +9
General-purpose robots require decision-making models that generalize across diverse tasks and environments. Recent works build robot foundation models by extending multimodal larg…
Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part II
Yi Tian, Kaiqing Zhang, Russ Tedrake +1
We study the problem of state representation learning for control from partial and potentially high-dimensional observations. We approach this problem via cost-driven state represe…
A Framework for Combining Optimization-Based and Analytic Inverse Kinematics
Thomas Cohn, Lihan Tang, Alexandre Amice +1
Analytic and optimization methods for solving inverse kinematics (IK) problems have been deeply studied throughout the history of robotics. The two strategies have complementary st…