How to Train Your Guide Dog: Wayfinding and Safe Navigation with Human-Robot Modeling

Abstract

A robot guide dog has the potential to enhance the independence and quality of life of individuals who are blind or visually impaired by providing accessible, automated, and intelligent guidance. However, developing effective robot guide dogs requires researchers not only to solve robotic perception and planning problems but also to understand complicated two-way interactions of the human-robot team. This work presents the formal definition of the wayfinding task of the robotic guide dog that is grounded by common practices in the real world. Given such a task, we train an effective policy for the robot guide dog while investigating two different human models, a rotating rod model and a rigid harness model. We show that our robot can safely guide a human user to avoid several obstacles in the real world. We also demonstrate that a proper human model is necessary to achieve collision-free navigation for both the human and the robot.