Learning an interpretable logic monitor for risk-aware and socially-compliant trajectory planning

Xiao Li, Jonathan DeCastro, Cristian-Ioan Vasile, Sertac Karaman, Daniela Rus, Computer Science and Artificial Intelligence Lab, Department of Mechanical Engineering, Shanghai Jiao Tong University, Toyota Research Institute, Los Altos, Department of Mechanical Engineering and Mechanics, Lehigh University, Laboratory for Information and Decision Systems

The International Journal of Robotics Research

Published online on November 03, 2025

Abstract

The International Journal of Robotics Research, Ahead of Print.
In order to plan robot behaviors effectively in the real world, it is often necessary to consider risks and learn from humans in dealing with them. We posit that humans manage risks by taking into consideration the nuances of the task that are specific to ...