Human Movement Prediction is Shared Human-Robot Workspaces

Manufacturing workspaces pose additional requirements as fleets of mobile vehicles are deployed alongside workers to jointly or independently perform activities. Breaking the clear separating zones provisioned in the past for automated guided vehicles and humans, safety and legal concerns must be addressed to make shared industrial workspaces both safe and productive.

This creates a need for research in socially-aware robot navigation to target also such deployments. To allow for safer and more efficient manufacturing operations in shared workspaces, it is important for robot fleet planning to anticipate human movement. The research related to the datasets here aims to explore and evaluate the extent to which a graph-based neural network approach can be applicable to predicting human occupancy in such workspaces based on past observations.