Browsing by Author "Amirshirzad, Negin"

Now showing items 1-6 of 6

Adaptive shared control with human intention estimation for human agent collaboration

Amirshirzad, Negin; Uğur, E.; Bebek, Özkan; Öztop, Erhan (IEEE, 2022)

In this paper an adaptive shared control frame-work for human agent collaboration is introduced. In this framework the agent predicts the human intention with a confidence factor that also serves as the control blending ...
Context based echo state networks for robot movement primitives

Amirshirzad, Negin; Asada, M.; Öztop, Erhan (IEEE, 2023)

Reservoir Computing, in particular Echo State Networks (ESNs) offer a lightweight solution for time series representation and prediction. An ESN is based on a discrete time random dynamical system that is used to output a ...
Human adaptation to human–robot shared control

Amirshirzad, Negin; Kumru, Asiye; Öztop, Erhan (IEEE, 2019-04)

Human-in-the-loop robot control systems naturally provide the means for synergistic human-robot collaboration through control sharing. The expectation in such a system is that the strengths of each partner are combined to ...
Human-robot collaboration for synergistic task execution

Amirshirzad, Negin (2017-05)

There is great potential for human and robot to work together as a team, since this collaboration can take advantage of both human and robot capabilities, cover their weakness and yield a higher performance. We propose and ...
Learning medical suturing primitives for autonomous suturing

Amirshirzad, Negin; Sunal, Begüm; Bebek, Özkan; Öztop, Erhan (IEEE, 2021)

This paper focuses on a learning from demonstration approach for autonomous medical suturing. A conditional neural network is used to learn and generate suturing primitives trajectories which were conditioned on desired ...
Synergistic human-robot shared control via human goal estimation

Amirshirzad, Negin; Kaya, Osman; Öztop, Erhan (IEEE, 2016)

In this paper, we propose and implement a synergistic human-robot collaboration framework, where the robotic system estimates the intent or goal of the human operator while being controlled by the human in real-time. Having ...