Papers › Automated acquisition of structured, semantic models of manipulation activities from...
Automated acquisition of structured, semantic models of manipulation activities from human VR demonstration
Andrei Haidu, Michael Beetz
In this paper we present a system capable of collecting and annotating, human performed, robot understandable, everyday activities from virtual environments. The human movements are mapped in the simulated world using off-the-shelf virtual reality devices with full body, and eye tracking capabilities. All the interactions in the virtual world are physically simulated, thus movements and their effects are closely relatable to the real world. During the activity execution, a subsymbolic data logger is recording the environment and the human gaze on a per-frame basis, enabling offline scene reproduction and replays. Coupled with the physics engine, online monitors (symbolic data loggers) are parsing (using various grammars) and recording events, actions, and their effects in the simulated world.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections