Andrew R. Barkan — accepted AI-conference papers

2021

Force-Sensing Tensegrity for Investigating Physical Human-Robot Interaction in Compliant Robotic Systems

Andrew R. Barkan, Akhil Padmanabha, Sala R. Tiemann, Albert Lee, Matthew P. Kanter, Yash S. Agarwal +1

ICRA 2021poster

Advancements in the domain of physical human-robot interaction (pHRI) have tremendously improved the ability of humans and robots to communicate, collaborate, and coexist. In particular, compliant robotic systems offer many characteristics that can be leveraged towards enabling physical interactions…

Cited by 9 Source ↗Scholar ↗

2020

Inverse Statics Optimization for Compound Tensegrity Robots

Andrew P. Sabelhaus, Albert H. Li, Kimberly A. Sover, Jacob R. Madden, Andrew R. Barkan, Adrian K. Agogino +1

RA-L 2020

Robots built from cable-driven tensegrity (`tension-integrity') structures have many of the advantages of soft robots, such as flexibility and robustness, yet still obey simple statics and dynamics models. However, existing approaches cannot natively model tensegrity robots with arbitrary rigid bodi

Cited by 33 Source ↗Scholar ↗