4 papers
Learning to Predict Contact Force Distributions from Vision Leveraging Object Geometry Priors
Ryo Hanai, Yukiyasu Domaea, Ixchel G. Ramirez-Alpizar +3
Based on vision and prior experience, humans can make rough physical predictions and adjust their manipulation strategies. This paper aims to endow robots with a similar ability. T…
Robust Instant Policy: Leveraging Student's t-Regression Model for Robust In-context Imitation Learning of Robot Manipulation
Hanbit Oh, Andrea M. Salcedo-Vázquez, Ixchel G. Ramirez-Alpizar +1
Imitation learning (IL) aims to enable robots to perform tasks autonomously by observing a few human demonstrations. Recently, a variant of IL, called In-Context IL, utilized off-t…
Breaking Down the Barriers: Investigating Non-Expert User Experiences in Robotic Teleoperation in UK and Japan
Florent P Audonnet, Andrew Hamilton, Yakiyasu Domae +2
Robots are being created each year with the goal of integrating them into our daily lives. As such, there is an interest in research in evaluating the trust of humans toward robots…
Visual Imitation Learning of Non-Prehensile Manipulation Tasks with Dynamics-Supervised Models
Abdullah Mustafa, Ryo Hanai, Ixchel Ramirez +4
Unlike quasi-static robotic manipulation tasks like pick-and-place, dynamic tasks such as non-prehensile manipulation pose greater challenges, especially for vision-based control.…