6 accepted papers
Shared autonomy methods, where a human operator and a robot arm work together, have enabled robots to complete a range of complex and highly variable tasks. Existing work primarily focuses on one human sharing autonomy with a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http:/
Many tasks, particularly those involving interaction with the environment, are characterized by high variability, making robotic autonomy difficult. One flexible solution is to introduce the input of a human with superior experience and cognitive abilities as part of a shared autonomy policy. Howeve
Manufacturing systems involve machines and people. Both productivity and ergonomic performance are of significant importance in manufacturing. However, there is no integrated model to analyze them simultaneously. To bridge this gap, a unified model is introduced to evaluate the productivity and ergo
Corrective Shared Autonomy is a method where human corrections are layered on top of an otherwise autonomous robot behavior. Specifically, a Corrective Shared Autonomy system leverages an external controller to allow corrections across a range of task variables (e.g., spinning speed of a tool, appli
The rapid development of machine learning (ML) technology has introduced substantial impact on ergonomics research in manufacturing. Numerous studies and practices have been carried out to apply ML techniques to address manufacturing ergonomics issues, which has brought extensive opportunities as we
Performance-cost trade-offs in video object tracking tasks for long video sequences is investigated. A novel frame-subsampled, drift-resilient (FSDR) video object tracking algorithm is presented that would achieve desired tracking accuracy while dramatically reducing computing time by processing onl…