THÖR-Magni (Demo Subset): a new multi-modal context-rich dataset of human-robot motion

The 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 induce natural behavior of recorded participants, we utilized loosely scripted task assignment, which induced participants to navigate through 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 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)