46 citations · 57 across the 12 of their papers we have counts for
12 papers
Adversarial Vulnerabilities of Learned Telesurgery Policies
Shutong Jin, Ziyang Chen, Preethi Satish +3
While not yet in clinical deployment, learning-based policies are increasingly considered to augment the dexterity of human surgeons in robot-assisted surgery. Can the end-to-end m…
MonoDuo: Using One Robot Arm to Learn Bimanual Policies
Sandeep Bajamahal, Lawrence Yunliang Chen, Toru Lin +3
Bimanual coordination is essential for many real-world manipulation tasks, yet learning bimanual robot policies is limited by the scarcity of bimanual robots and datasets. Single-a…
OXE-AugE: A Large-Scale Robot Augmentation of OXE for Scaling Cross-Embodiment Policy Learning
Guanhua Ji, Harsha Polavaram, Lawrence Yunliang Chen +5
Large and diverse datasets are needed for training generalist robot policies that have potential to control a variety of robot embodiments -- robot arm and gripper combinations --…
Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets
Kaiyuan Chen, Shuangyu Xie, Zehan Ma +2
Vision-Language Models (VLMs) acquire real-world knowledge and general reasoning ability through Internet-scale image-text corpora. They can augment robotic systems with scene unde…
Breathless: An 8-hour Performance Contrasting Human and Robot Expressiveness
Catie Cuan, Tianshuang Qiu, Shreya Ganti +1
This paper describes the robot technology behind an original performance that pairs a human dancer (Cuan) with an industrial robot arm for an eight-hour dance that unfolds over the…
Mirage: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting
Lawrence Yunliang Chen, Kush Hari, Karthik Dharmarajan +3
The ability to reuse collected data and transfer trained policies between robots could alleviate the burden of additional data collection and training. While existing approaches su…
Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features
Justin Kerr, Huang Huang, Albert Wilcox +4
Humans make extensive use of vision and touch as complementary senses, with vision providing global information about the scene and touch measuring local information during manipul…
Autonomously Untangling Long Cables
Vainavi Viswanath, Kaushik Shivakumar, Justin Kerr +7
Cables are ubiquitous in many settings and it is often useful to untangle them. However, cables are prone to self-occlusions and knots, making them difficult to perceive and manipu…
DayDreamer: World Models for Physical Robot Learning
Philipp Wu, Alejandro Escontrela, Danijar Hafner +2
To solve tasks in complex environments, robots need to learn from experience. Deep reinforcement learning is a common approach to robot learning but requires a large amount of tria…
Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision
Ryan Hoque, Lawrence Yunliang Chen, Satvik Sharma +4
Commercial and industrial deployments of robot fleets at Amazon, Nimble, Plus One, Waymo, and Zoox query remote human teleoperators when robots are at risk or unable to make task p…
Efficiently Learning Single-Arm Fling Motions to Smooth Garments
Lawrence Yunliang Chen, Huang Huang, Ellen Novoseller +6
Recent work has shown that 2-arm "fling" motions can be effective for garment smoothing. We consider single-arm fling motions. Unlike 2-arm fling motions, which require little robo…
Multi-Object Grasping in the Plane
Wisdom C. Agboh, Jeffrey Ichnowski, Ken Goldberg +1
We consider a novel problem where multiple rigid convex polygonal objects rest in randomly placed positions and orientations on a planar surface visible from an overhead camera. Th…