6 accepted papers
The imitation learning paradigm is a systematic approach for encoding intelligent behaviors into robotic systems. While a model representation of the ideal task behavior can be learned by processing a set of human demonstrations, learning a modeling representation that can generalize the desired beh
Often in the field of haptic guidance, an important question is how the robotic device should assist some imperfect human movement. While many control strategies have been suggested to help improve human performance in particular tasks, structuring guidance in a generalizable way remains elusive. Ma…
Surgical activity recognition and prediction can help provide important context in many Robot-Assisted Surgery (RAS) applications, for example, surgical progress monitoring and estimation, surgical skill evaluation, and shared control strategies during teleoperation. Transformer models were first de…
An important problem in designing human-robot systems is the integration of human intent and performance in the robotic control loop, especially during complex tasks. Bimanual coordination is a complex human behavior that is critical in many fine motor tasks, including robot-assisted surgery. To ful…
The effectiveness of control algorithms for teleoperated systems is typically evaluated through experimental performance measures, post-experimental user surveys, and theoretical analysis. However, none of these methods provide an objective assessment of teleoperation algorithms with respect to the…