Dr. Nick Gans, Principal Research Scientist and head of UTARI’s Automation and Intelligent Systems Division, was accepted in early access by The Institute of Electrical and Electronics Engineers (IEEE). The paper “Rule-Based Safe Probabilistic Movement Primitive Control via Control Barrier Functions,” has been finalized and posted in “Early Access.” In the paper, researchers developed a novel and safe control design approach that takes demonstrations provided by a human teacher to enable a robot to accomplish complex manipulation scenarios in dynamic environments. The paper is an extension of previous work that was a finalist for the 2021 Best Paper at IEEE Conference on Automation Science and Engineering.
The collaborative team includes Dr. Nick Gans, UTARI, Dr. Bill Beksi, UTA, Dr. Mohammadreza Davoodi, UTARI and University of Memphis, Dr. Asif Iqbal, UTARI, Joe Cloud, UTA.
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