Deep Learning Framework for Controlling Work Sequence in Collaborative Human-Robot Assembly Processes.

ABSTRACT: The human-robot collaboration (HRC) solutions presented so far have the disadvantage that the interaction between humans and robots is based on the human's state or on specific gestures purposely performed by the human, thus increasing the time required to perform a task and slowing down the pace of human labor, making such solutions uninteresting. In this study, a different concept of the HRC system is introduced, consisting of an HRC framework for managing assembly processes that are executed simultaneously or individually by humans and robots. This HRC framework based on deep learning models uses only one type of data, RGB camera data, to make predictions about the collaborative workspace and human action, and consequently manage the assembly process. To validate the HRC framework, an i

SUBMITTER: Garcia PP 

PROVIDER: S-EPMC9823442 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature