AUTHOR=Mielke Erich , Townsend Eric , Wingate David , Salmon John L. , Killpack Marc D. TITLE=Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads JOURNAL=Frontiers in Neurorobotics VOLUME=18 YEAR=2024 URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2024.1291694 DOI=10.3389/fnbot.2024.1291694 ISSN=1662-5218 ABSTRACT=

Human teams are able to easily perform collaborative manipulation tasks. However, simultaneously manipulating a large extended object for a robot and human is a difficult task due to the inherent ambiguity in the desired motion. Our approach in this paper is to leverage data from human-human dyad experiments to determine motion intent for a physical human-robot co-manipulation task. We do this by showing that the human-human dyad data exhibits distinct torque triggers for a lateral movement. As an alternative intent estimation method, we also develop a deep neural network based on motion data from human-human trials to predict future trajectories based on past object motion. We then show how force and motion data can be used to determine robot control in a human-robot dyad. Finally, we compare human-human dyad performance to the performance of two controllers that we developed for human-robot co-manipulation. We evaluate these controllers in three-degree-of-freedom planar motion where determining if the task involves rotation or translation is ambiguous.