Update 2025: JOURNAL AVAILABLE NOW: HEREFULL DATASET AVAILABLE: HEREThe Magni Human Motion Dataset provides high-quality tracking information from motion capture, eye-gaze trackers, and on-board robot sensors in a semantically rich environment. To elicit natural behavior from recorded participants, we used loosely scripted task assignments that prompted them to navigate a dynamic laboratory environment in a natural and purposeful way. The dataset sets a high-quality standard as realistic and accurate data is enhanced with semantic information, enabling the development of new algorithms that rely not only on tracking information but also on contextual cues of moving agents, static, and dynamic environments. Link to dashboard that uses the data: https://magni-dash.streamlit.app/ Here we publish a subset of the final dataset to accompany the presentation at the 2023 IEEE International Conference on Robotics and Automation (ICRA)

Other authors: Yufei Zhu, Eduardo Gutierrez Maestro, Lucas Morillo-Mendez, Andrey Rudenko, Tomasz P. Kucner, Oscar Martinez Mozos, Martin Magnusson, Luigi Palmieri, Kai O. Arras, Achim J. Lilienthal