3 accepted papers
This paper presents an error-state Model Predictive Path Integral (MPPI) framework for tendon-driven continuum robots (TDCRs). Tracking-error dynamics are formulated on a Lie group to preserve full pose geometry, yielding precise position-orientation error metrics. A nonlinear Cosserat-rod model wit
Modeling concentric tube robots (CTRs) involves complex nonlinear continuum mechanics, and despite recent progress, physics-based models often lack an accurate representation of the experimental setups. To overcome these limitations, deep neural network-based models have been explored as alternative…
Accurately estimating tool-tissue interaction forces during robotics-assisted minimally invasive surgery is an important aspect of enabling haptics-based teleoperation. By collecting data regarding the state of a robot in a variety of configurations, neural networks can be trained to predict this in