activity
20182022
most citedLearning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data

16 citations · 57 across the 11 of their papers we have counts for

collaborators

20 papers

cs.CV20225 cited

All You Need is LUV: Unsupervised Collection of Labeled Images using Invisible UV Fluorescent Indicators

Brijen Thananjeyan, Justin Kerr, Huang Huang +2

Large-scale semantic image annotation is a significant challenge for learning-based perception systems in robotics. Current approaches often rely on human labelers, which can be ex…

cs.LG20212 cited

LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Sparse Reward Iterative Tasks

Albert Wilcox, Ashwin Balakrishna, Brijen Thananjeyan +2

Reinforcement learning (RL) has shown impressive success in exploring high-dimensional environments to learn complex tasks, but can often exhibit unsafe behaviors and require exten…

cs.RO202114 cited

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo

Thomas Kollar, Michael Laskey, Kevin Stone +2

Robot manipulation of unknown objects in unstructured environments is a challenging problem due to the variety of shapes, materials, arrangements and lighting conditions. Even with…

cs.RO2021

Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies

Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan +7

Robot manipulation for untangling 1D deformable structures such as ropes, cables, and wires is challenging due to their infinite dimensional configuration space, complex dynamics,…

cs.LG20211 cited

PAC Best Arm Identification Under a Deadline

Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica +3

We study -PAC best arm identification, where a decision-maker must identify an -optimal arm with probability at least , while minimizing the number of arm pulls (…

cs.RO20212 cited

Disentangling Dense Multi-Cable Knots

Vainavi Viswanath, Jennifer Grannen, Priya Sundaresan +7

Disentangling two or more cables requires many steps to remove crossings between and within cables. We formalize the problem of disentangling multiple cables and present an algorit…