@inproceedings{8fac1bb8fccd458798fde0f1d8c869b9,
title = "Gesture-Based Feedback in Human-Robot Interaction for Object Manipulation",
abstract = "Human-Robot Interaction is a currently highly active research area with many advances in interfaces that allow humans and robots to have bi-directional feedback of their intentions. However, in an industrial setting, current robot feedback methods struggle to successfully deliver messages since the environment makes it difficult and inconvenient for the user to perceive them. This paper proposes a novel method for robot feedback, leveraging the addition of social cues to robot movement to notify the human of its intentions. Through the use of robotic gestures, we believe it is possible to successfully convey the robots{\textquoteright} goals in interactions with humans. To verify this hypothesis, a proof of concept was developed in a simulated environment using a robotic arm manipulator that notifies the user using gestures when it needs to correct the pose of an object.",
keywords = "Human-Robot Interaction, Machine Learning, Object manipulation, Robotics, Simulation",
author = "Leandro Filipe and Peres, {Ricardo Silva} and Francisco Marques and Jos{\'e} Barata",
note = "Publisher Copyright: {\textcopyright} 2022, IFIP International Federation for Information Processing.; 13th Advanced Doctoral Conference on Computing, Electrical, and Industrial Systems, DoCEIS 2022 ; Conference date: 29-06-2022 Through 01-07-2022",
year = "2022",
doi = "10.1007/978-3-031-07520-9_12",
language = "English",
isbn = "978-3-031-07519-3",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer",
pages = "122--132",
editor = "Camarinha-Matos, {Lu{\'i}s M.}",
booktitle = "Technological Innovation for Digitalization and Virtualization",
address = "Netherlands",
}