Search Results for author: Michael Danielczuk

Found 9 papers, 3 papers with code

Object Rearrangement Using Learned Implicit Collision Functions

1 code implementation21 Nov 2020 Michael Danielczuk, Arsalan Mousavian, Clemens Eppner, Dieter Fox

The learned model outperforms both traditional pipelines and learned ablations by 9. 8% in accuracy on a dataset of simulated collision queries and is 75x faster than the best-performing baseline.

Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects

no code implementations11 Nov 2020 Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Shivin Devgon, Ken Goldberg

However, these policies can consistently fail to grasp challenging objects which are significantly out of the distribution of objects in the training data or which have very few high quality grasps.

Accelerating Grasp Exploration by Leveraging Learned Priors

no code implementations11 Nov 2020 Han Yu Li, Michael Danielczuk, Ashwin Balakrishna, Vishal Satish, Ken Goldberg

The ability of robots to grasp novel objects has industry applications in e-commerce order fulfillment and home service.

Non-Markov Policies to Reduce Sequential Failures in Robot Bin Picking

no code implementations20 Jul 2020 Kate Sanders, Michael Danielczuk, Jeffrey Mahler, Ajay Tanwani, Ken Goldberg

A new generation of automated bin picking systems using deep learning is evolving to support increasing demand for e-commerce.

X-Ray: Mechanical Search for an Occluded Object by Minimizing Support of Learned Occupancy Distributions

no code implementations20 Apr 2020 Michael Danielczuk, Anelia Angelova, Vincent Vanhoucke, Ken Goldberg

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.

GOMP: Grasp-Optimized Motion Planning for Bin Picking

no code implementations5 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).


Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter

no code implementations4 Mar 2019 Michael Danielczuk, Andrey Kurenkov, Ashwin Balakrishna, Matthew Matl, David Wang, Roberto Martín-Martín, Animesh Garg, Silvio Savarese, Ken Goldberg

In this paper, we formalize Mechanical Search and study a version where distractor objects are heaped over the target object in a bin.


Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data

2 code implementations16 Sep 2018 Michael Danielczuk, Matthew Matl, Saurabh Gupta, Andrew Li, Andrew Lee, Jeffrey Mahler, Ken Goldberg

We train a variant of Mask R-CNN with domain randomization on the generated dataset to perform category-agnostic instance segmentation without any hand-labeled data and we evaluate the trained network, which we refer to as Synthetic Depth (SD) Mask R-CNN, on a set of real, high-resolution depth images of challenging, densely-cluttered bins containing objects with highly-varied geometry.

Object Tracking Semantic Segmentation +1

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