Formalizing a Transient-Goal Driven Approach for Pedestrian-Aware Robot Navigation

Abstract

In this paper, we lay the algorithmic foundations of a unifying strategy for pedestrian-aware navigation that is aimed at service/social robots deployed in large human-crowded environments. In order to accommodate both modeled and learned social navigation behaviors, we formalize an approach within which the robot traverses to a specific goal (or sub-goal) via a trajectory of optimal transient-goals or optimal short-term way-points. We then evaluate an implementation of the navigation strategy, by utilizing an augmented Risk-based Rapidly Exploring Random Trees (RRT) planner, and demonstrate its efficacy for real-world deployment using discriminative simulations and by providing avenues for future work.