Kyle DuFrene — accepted AI-conference papers

2024

The Grasp Reset Mechanism: An Automated Apparatus for Conducting Grasping Trials

Kyle DuFrene, Keegan Nave, Joshua Campbell, Ravi Balasubramanian, Cindy Grimm

ICRA 2024poster

Advancing robotic grasping and manipulation requires the ability to test algorithms and/or train learning models on large numbers of grasps. Towards the goal of more advanced grasping, we present the Grasp Reset Mechanism (GRM), a fully automated apparatus for conducting large-scale grasping trials.…

Cited by 3 Source ↗Scholar ↗

2023

Hand Design Approach for Planar Fully Actuated Manipulators

Keegan Nave, Kyle DuFrene, Nigel Swenson, Ravi Balasubramanian, Cindy Grimm

IROS 2023poster

Robotic in-hand manipulation increases the capability of robotic hands to interact with the world. The amount of manipulation that a robot is capable of is highly dependent on the design of the robot hand, and previous works have shown success in designing hands to improve performance for different…

Cited by 3 Source ↗Scholar ↗