Connor L. Yako — accepted AI-conference papers

2022

Designing Underactuated Graspers with Dynamically Variable Geometry Using Potential Energy Map Based Analysis

Connor L. Yako, Shenli Yuan, J. Kenneth Salisbury

IROS 2022poster

In this paper we present a potential energy map based approach that provides a framework for the design and control of a robotic grasper. Unlike other potential energy map approaches, our framework considers friction for a more realistic perspective on grasper performance. Our analysis establishes t…

Cited by 7 Source ↗Scholar ↗

2020

Design and Control of Roller Grasper V2 for In-Hand Manipulation

Shenli Yuan, Lin Shao, Connor L. Yako, Alex Gruebele, J. Kenneth Salisbury

IROS 2020poster

The ability to perform in-hand manipulation still remains an unsolved problem; having this capability would allow robots to perform sophisticated tasks requiring repositioning and reorienting of grasped objects. In this work, we present a novel non-anthropomorphic robot grasper with the ability to m…

Cited by 57 Source ↗Scholar ↗