no code implementations • 13 Oct 2022 • Wisdom C. Agboh, Satvik Sharma, Kishore Srinivas, Mallika Parulekar, Gaurav Datta, Tianshuang Qiu, Jeffrey Ichnowski, Eugen Solowjow, Mehmet Dogar, Ken Goldberg
In physical experiments, we find a 13. 7% increase in success rate, a 1. 6x increase in picks per hour, and a 6. 3x decrease in grasp planning time compared to prior work on multi-object grasping.
no code implementations • 27 Sep 2022 • Kaushik Shivakumar, Vainavi Viswanath, Anrui Gu, Yahav Avigal, Justin Kerr, Jeffrey Ichnowski, Richard Cheng, Thomas Kollar, Ken Goldberg
Cables are commonplace in homes, hospitals, and industrial warehouses and are prone to tangling.
no code implementations • 16 Jul 2022 • Vainavi Viswanath, Kaushik Shivakumar, Justin Kerr, Brijen Thananjeyan, Ellen Novoseller, Jeffrey Ichnowski, Alejandro Escontrela, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg
Cables are ubiquitous in many settings and it is often useful to untangle them.
no code implementations • 1 Jun 2022 • Wisdom C. Agboh, Jeffrey Ichnowski, Ken Goldberg, Mehmet R. Dogar
In physical grasping experiments comparing performance with a single-object picking baseline, we find that the frictionless multi-object grasping system achieves 13. 6\% higher grasp success and is 59. 9\% faster, from 212 PPH to 340 PPH.
no code implementations • 8 Mar 2022 • Vincent Lim, Ellen Novoseller, Jeffrey Ichnowski, Huang Huang, Ken Goldberg
For applications in healthcare, physics, energy, robotics, and many other fields, designing maximally informative experiments is valuable, particularly when experiments are expensive, time-consuming, or pose safety hazards.
no code implementations • 22 Jan 2022 • Huang Huang, Michael Danielczuk, Chung Min Kim, Letian Fu, Zachary Tam, Jeffrey Ichnowski, Anelia Angelova, Brian Ichter, Ken Goldberg
Shelves are common in homes, warehouses, and commercial settings due to their storage efficiency.
1 code implementation • 27 Oct 2021 • Jeffrey Ichnowski, Yahav Avigal, Justin Kerr, Ken Goldberg
The ability to grasp and manipulate transparent objects is a major challenge for robots.
1 code implementation • NeurIPS 2021 • Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg
First-order methods for quadratic optimization such as OSQP are widely used for large-scale machine learning and embedded optimal control, where many related problems must be rapidly solved.
1 code implementation • 13 Jul 2021 • Shivin Devgon, Jeffrey Ichnowski, Michael Danielczuk, Daniel S. Brown, Ashwin Balakrishna, Shirin Joshi, Eduardo M. C. Rocha, Eugen Solowjow, Ken Goldberg
In industrial part kitting, 3D objects are inserted into cavities for transportation or subsequent assembly.
no code implementations • 29 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.
no code implementations • 4 Jun 2021 • Vainavi Viswanath, Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Ellen Novoseller, Jeffrey Ichnowski, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg
Disentangling two or more cables requires many steps to remove crossings between and within cables.
no code implementations • 29 May 2021 • Shivin Devgon, Jeffrey Ichnowski, Ashwin Balakrishna, Harry Zhang, Ken Goldberg
We formulate a self-supervised objective for this problem and train a deep neural network to estimate the 3D rotation as parameterized by a quaternion, between these current and desired depth images.
no code implementations • 23 Dec 2020 • Minho Hwang, Brijen Thananjeyan, Daniel Seita, Jeffrey Ichnowski, Samuel Paradis, Danyal Fer, Thomas Low, Ken Goldberg
Peg transfer is a well-known surgical training task in the Fundamentals of Laparoscopic Surgery (FLS).
no code implementations • 10 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.
no code implementations • 10 Nov 2020 • Harry Zhang, Jeffrey Ichnowski, Daniel Seita, Jonathan Wang, Huang Huang, Ken Goldberg
The framework finds a 3D apex point for the robot arm, which, together with a task-specific trajectory function, defines an arcing motion that dynamically manipulates the cable to perform tasks with varying obstacle and target locations.
no code implementations • 19 Mar 2020 • Minho Hwang, Brijen Thananjeyan, Samuel Paradis, Daniel Seita, Jeffrey Ichnowski, Danyal Fer, Thomas Low, Ken Goldberg
Automation of surgical subtasks using cable-driven robotic surgical assistants (RSAs) such as Intuitive Surgical's da Vinci Research Kit (dVRK) is challenging due to imprecision in control from cable-related effects such as cable stretching and hysteresis.
no code implementations • 5 Mar 2020 • Jeffrey Ichnowski, Michael Danielczuk, Jingyi Xu, Vishal Satish, Ken Goldberg
Rapid and reliable robot bin picking is a critical challenge in automating warehouses, often measured in picks-per-hour (PPH).
no code implementations • 15 Feb 2020 • Minho Hwang, Daniel Seita, Brijen Thananjeyan, Jeffrey Ichnowski, Samuel Paradis, Danyal Fer, Thomas Low, Ken Goldberg
We report experimental results for a handover-free version of the peg transfer task, performing 20 and 5 physical episodes with single- and bilateral-arm setups, respectively.
1 code implementation • 23 Sep 2019 • Daniel Seita, Aditya Ganapathi, Ryan Hoque, Minho Hwang, Edward Cen, Ajay Kumar Tanwani, Ashwin Balakrishna, Brijen Thananjeyan, Jeffrey Ichnowski, Nawid Jamali, Katsu Yamane, Soshi Iba, John Canny, Ken Goldberg
In 180 physical experiments with the da Vinci Research Kit (dVRK) surgical robot, RGBD policies trained in simulation attain coverage of 83% to 95% depending on difficulty tier, suggesting that effective fabric smoothing policies can be learned from an algorithmic supervisor and that depth sensing is a valuable addition to color alone.