Christopher Ninatanta — accepted AI-conference papers

2024

Modeling and Experimental Verification of a Continuous Curvature-Based Soft Growing Manipulator

Justin Allen, Ryan Dorosh, Christopher Ninatanta, Andrew Allen, Linlin Shui, Kyle T. Yoshida +2

RA-L 2024

Soft robots show significant potential for use in search and rescue, human-robot interaction, and other emerging fields due to their ability to easily conform, deform, and interact with their environment. However, precise control of these soft robots is still being explored. In this letter, we inves

Cited by 8 Source ↗Scholar ↗

2023

Design, Modeling, and Control of a Low-Cost and Rapid Response Soft-Growing Manipulator for Orchard Operations

Ryan Dorosh, Justin Allen, Zixuan He, Christopher Ninatanta, Jack Coleman, Jack Spieker +7

IROS 2023poster

Tree fruit growers around the world are facing labor shortages for critical operations, including harvest and pruning. There is a great interest in developing robotic solutions for these labor-intensive tasks, but current efforts have been prohibitively costly, slow, or require a reconfiguration of…

Cited by 3 Source ↗Scholar ↗