108 citations · 150 across the 18 of their papers we have counts for
19 papers
Mechanical Search on Shelves with Efficient Stacking and Destacking of Objects
Huang Huang, Letian Fu, Michael Danielczuk +6
Stacking increases storage efficiency in shelves, but the lack of visibility and accessibility makes the mechanical search problem of revealing and extracting target objects diffic…
Optimal Shelf Arrangement to Minimize Robot Retrieval Time
Lawrence Yunliang Chen, Huang Huang, Michael Danielczuk +2
Shelves are commonly used to store objects in homes, stores, and warehouses. We formulate the problem of Optimal Shelf Arrangement (OSA), where the goal is to optimize the arrangem…
FogROS2: An Adaptive Platform for Cloud and Fog Robotics Using ROS 2
Jeffrey Ichnowski, Kaiyuan Chen, Karthik Dharmarajan +12
Mobility, power, and price points often dictate that robots do not have sufficient computing power on board to run contemporary robot algorithms at desired rates. Cloud computing p…
Mechanical Search on Shelves using a Novel "Bluction" Tool
Huang Huang, Michael Danielczuk, Chung Min Kim +6
Shelves are common in homes, warehouses, and commercial settings due to their storage efficiency. However, this efficiency comes at the cost of reduced visibility and accessibility…
LEGS: Learning Efficient Grasp Sets for Exploratory Grasping
Letian Fu, Michael Danielczuk, Ashwin Balakrishna +4
While deep learning has enabled significant progress in designing general purpose robot grasping systems, there remain objects which still pose challenges for these systems. Recent…
IPC-GraspSim: Reducing the Sim2Real Gap for Parallel-Jaw Grasping with the Incremental Potential Contact Model
Chung Min Kim, Michael Danielczuk, Isabella Huang +1
Accurately simulating whether an object will be lifted securely or dropped during grasping is a longstanding Sim2Real challenge. Soft compliant jaw tips are almost universally used…