108 citations · 150 across the 18 of their papers we have counts for
7 papers · 1 filter
Mechanical Search on Shelves using Lateral Access X-RAY
Huang Huang, Marcus Dominguez-Kuhne, Jeffrey Ichnowski +7
Efficiently finding an occluded object with lateral access arises in many contexts such as warehouses, retail, healthcare, shipping, and homes. We introduce LAX-RAY (Lateral Access…
Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects
Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown +2
There has been significant recent work on data-driven algorithms for learning general-purpose grasping policies. However, these policies can consistently fail to grasp challenging…
Accelerating Grasp Exploration by Leveraging Learned Priors
Han Yu Li, Michael Danielczuk, Ashwin Balakrishna +2
The ability of robots to grasp novel objects has industry applications in e-commerce order fulfillment and home service. Data-driven grasping policies have achieved success in lear…
Object Rearrangement Using Learned Implicit Collision Functions
Michael Danielczuk, Arsalan Mousavian, Clemens Eppner +1
Robotic object rearrangement combines the skills of picking and placing objects. When object models are unavailable, typical collision-checking models may be unable to predict coll…
Non-Markov Policies to Reduce Sequential Failures in Robot Bin Picking
Kate Sanders, Michael Danielczuk, Jeffrey Mahler +2
A new generation of automated bin picking systems using deep learning is evolving to support increasing demand for e-commerce. To accommodate a wide variety of products, many autom…
X-Ray: Mechanical Search for an Occluded Object by Minimizing Support of Learned Occupancy Distributions
Michael Danielczuk, Anelia Angelova, Vincent Vanhoucke +1
For applications in e-commerce, warehouses, healthcare, and home service, robots are often required to search through heaps of objects to grasp a specific target object. For mechan…