1 citations · 1 across the 13 of their papers we have counts for
17 papers
StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras
Jason Chen, I-Chun Arthur Liu, Gaurav Sukhatme +1
Stereo vision is increasingly used for robotic manipulation, with a growing body of work incorporating it into Vision-Language-Action (VLA) models. However, the scarcity of large-s…
ExStereo: Lifting 2D Vision-Language-Action Models to 3D with Explicit Stereo Representations
I-Chun Arthur Liu, Jason Chen, Gaurav S. Sukhatme +1
Three-dimensional perception is critical for robotic manipulation, particularly for high-precision tasks, as recovering metric depth and precise 3D object positions from monocular…
Bundled Contact Gradients: Stabilizing Differentiable Simulation for Deployable Dynamic Tasks
Dyuman Aditya, Jin Cheng, Clemens Schwarke +4
Differentiable simulation provides analytic gradients of robot dynamics, enabling fast and sample-efficient first-order policy optimization. However, obtaining smooth and informati…
Rolling-WAM: World Action Models with Rolling Imagination
Yinghua Zhou, Junjie Ye, Yiqi Zhao +8
World Action Models (WAMs) couple action generation with future visual prediction for robotic manipulation. However, completing the joint video-action denoising process at each rep…
Duet: Dual-Robot Understanding via Efficient Teaching
Yiqi Zhao, Ruohai Ge, Celina Shiyu Wang +10
Dual-robot collaboration enables tasks that exceed the reach and payload of a single robot, such as collaboratively transporting objects across environments and executing coordinat…
Steering Multirobot Behavior via Closed-Loop Affine Activation Editing
Satyajeet Das, Darren Chiu, Shashank Hegde +1
Real-world robots need to adapt their behavior beyond the envelope of their pre-trained policy. Policy finetuning or retraining are options, but they risk catastrophic forgetting,…
Colosseum V2: Benchmarking Generalization for Vision-Language-Action Models
Jeremy Morgan, Prajwal Vijay, Hyeonho Oh +7
Vision-Language-Action (VLA) models demonstrate promising generalization in robotic manipulation, driven by advances in large-scale vision and language pre-training. This progress…
CRAFT: Video Diffusion for Bimanual Robot Data Generation
Jason Chen, I-Chun Arthur Liu, Gaurav Sukhatme +1
Bimanual robot learning from demonstrations is fundamentally limited by the cost and narrow visual diversity of real-world data, which constrains policy robustness across viewpoint…
HANDFUL: Sequential Grasp-Conditioned Dexterous Manipulation with Resource Awareness
Ethan Foong, Yunshuang Li, Hao Jiang +2
Dexterous robot hands offer rich opportunities for multifunctional manipulation, where a robot must execute multiple skills in sequence while maintaining control over previously gr…
Concurrent Prehensile and Nonprehensile Manipulation: A Practical Approach to Multi-Stage Dexterous Tasks
Hao Jiang, Yue Wu, Yue Wang +2
Dexterous hands enable concurrent prehensile and nonprehensile manipulation, such as holding one object while interacting with another, a capability essential for everyday tasks ye…
ROPA: Synthetic Robot Pose Generation for RGB-D Bimanual Data Augmentation
Jason Chen, I-Chun Arthur Liu, Gaurav Sukhatme +1
Training robust bimanual manipulation policies via imitation learning requires demonstration data with broad coverage over robot poses, contacts, and scene contexts. However, colle…
Learning Geometry-Aware Nonprehensile Pushing and Pulling with Dexterous Hands
Yunshuang Li, Yiyang Ling, Gaurav S. Sukhatme +1
Nonprehensile manipulation, such as pushing and pulling, enables robots to move, align, or reposition objects that may be difficult to grasp due to their geometry, size, or relatio…
Zero-Shot Visual Generalization in Robot Manipulation
Sumeet Batra, Gaurav Sukhatme
Training vision-based manipulation policies that are robust across diverse visual environments remains an important and unresolved challenge in robot learning. Current approaches o…
D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation
I-Chun Arthur Liu, Jason Chen, Gaurav Sukhatme +1
Learning bimanual manipulation is challenging due to its high dimensionality and tight coordination required between two arms. Eye-in-hand imitation learning, which uses wrist-moun…
Zero-Shot Generalization of Vision-Based RL Without Data Augmentation
Sumeet Batra, Gaurav S. Sukhatme
Generalizing vision-based reinforcement learning (RL) agents to novel environments remains a difficult and open challenge. Current trends are to collect large-scale datasets or use…
Quality Diversity for Robot Learning: Limitations and Future Directions
Sumeet Batra, Bryon Tjanaka, Stefanos Nikolaidis +1
Quality Diversity (QD) has shown great success in discovering high-performing, diverse policies for robot skill learning. While current benchmarks have led to the development of po…
VoxAct-B: Voxel-Based Acting and Stabilizing Policy for Bimanual Manipulation
I-Chun Arthur Liu, Sicheng He, Daniel Seita +1
Bimanual manipulation is critical to many robotics applications. In contrast to single-arm manipulation, bimanual manipulation tasks are challenging due to higher-dimensional actio…