Adaptable Human Intention and Trajectory Prediction for Human-Robot Collaboration

Understand

To engender safe and efficient human-robot collaboration, it is critical to generate high-fidelity predictions of human behavior.

• The challenges in making accurate predictions lie in the stochasticity and heterogeneity in human behaviors.
• This paper introduces a method for human trajectory and intention prediction through a multi-task model that is adaptable across different human subjects.
• We develop a nonlinear recursive least square parameter adaptation algorithm (NRLS-PAA) to achieve online adaptation.