Michael Fulton, PhD

Michael Fulton, PhD

Robotics software developer and researcher. I work on complex problems in marine robotics.

RCVM paper accepted for publication in THRI

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Published:

I’m happy to announce that my paper with Chelsey Edge and Junaed Sattar on the method of robot body language communication method I created: Robot Communication Via Motion (RCVM) has been accepted for publication in an upcoming issue of ACM Transactions on Human-Robot Interaction! This paper is nearly 40 pages, and was a labor of love: three studies are described in this paper including a very arduous evaluation of the effect of viewpoint, message content, and robot domain on the effectiveness of RCVM and other communication methods. The paper will be available at some time in the future at https://dl.acm.org/doi/10.1145/3495245

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HREye paper accepted at ICRA 2023

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I’m pleased to announce that my paper “HREyes: Design, Development, and Evaluation of a Novel Method for AUVs to Communicate Information and Gaze Direction”, has been accepted for publication at ICRA 2023! While I won’t be able to attend due to my impending graduation, I am overjoyed that this paper has been published, particularly given that this was a first attempt at publishing this paper. Read more

Award Result at IROS 2022

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Unfortunately, our paper “Robotic Detection of a Human-Comprehensible Gestural Language for Underwater Multi-Human-Robot Collaboration” did not win best Cognitive Robotics paper at IROS 2022. Congratulations to the other finalists and, of course, the winner! Read more

R2RCVM accepted at IROS 2022

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I’m excited to announce that my paper with Sadman Sakib Enan on Robot-to-Robot Communication via Motion has been accepted for publication at IROS 2022, in Kyoto. I’m even more excited to announce that it’s a finalist for the best paper in Cognitive Robotics! I won’t be attending, but I’m looking forward to the presentation of this paper. Enan developed R2RCVM based on my original implementation of RCVM, and I helped to evaluate his new version by determining that human participants could accurately transcribe gestural conversations between robots. Read more