Search Results for author: Jennifer Grannen

Found 6 papers, 1 papers with code

Detecting Damage Building Using Real-time Crowdsourced Images and Transfer Learning

1 code implementation12 Oct 2021 Gaurav Chachra, Qingkai Kong, Jim Huang, Srujay Korlakunta, Jennifer Grannen, Alexander Robson, Richard Allen

After significant earthquakes, we can see images posted on social media platforms by individuals and media agencies owing to the mass usage of smartphones these days.

Transfer Learning

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

no code implementations29 Jun 2021 Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Jeffrey Ichnowski, Ellen Novoseller, Minho Hwang, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg

We present two algorithms that enhance robust cable untangling, LOKI and SPiDERMan, which operate alongside HULK, a high-level planner from prior work.

Untangling Dense Knots by Learning Task-Relevant Keypoints

no code implementations10 Nov 2020 Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna, Minho Hwang, Vainavi Viswanath, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg

HULK successfully untangles a cable from a dense initial configuration containing up to two overhand and figure-eight knots in 97. 9% of 378 simulation experiments with an average of 12. 1 actions per trial.

Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data

no code implementations3 Mar 2020 Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Michael Laskey, Kevin Stone, Joseph E. Gonzalez, Ken Goldberg

We address these challenges using interpretable deep visual representations for rope, extending recent work on dense object descriptors for robot manipulation.

Visual Reasoning

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