Group Surfing: A Pedestrian-Based Approach to Sidewalk Robot Navigation

TL;DR

This paper introduces a novel pedestrian-aware navigation system for sidewalk robots, combining group surfing and sidewalk edge detection to navigate safely and socially in pedestrian-rich environments, validated through simulation and hardware tests.

Contribution

The paper presents a new group surfing method for sidewalk robot navigation that mimics pedestrian groups and a sidewalk edge detection approach for sparse environments, enhancing safety and social compliance.

Findings

Effective in simulation for pedestrian-rich environments

Successful hardware demonstration of navigation system

Improved safety and social compliance in navigation

Abstract

In this paper, we propose a novel navigation system for mobile robots in pedestrian-rich sidewalk environments. Sidewalks are unique in that the pedestrian-shared space has characteristics of both roads and indoor spaces. Like vehicles on roads, pedestrian movement often manifests as linear flows in opposing directions. On the other hand, pedestrians also form crowds and can exhibit much more random movements than vehicles. Classical algorithms are insufficient for safe navigation around pedestrians and remaining on the sidewalk space. Thus, our approach takes advantage of natural human motion to allow a robot to adapt to sidewalk navigation in a safe and socially-compliant manner. We developed a \textit{group surfing} method which aims to imitate the optimal pedestrian group for bringing the robot closer to its goal. For pedestrian-sparse environments, we propose a sidewalk edge detection and following method. Underlying these two navigation methods, the collision avoidance scheme is human-aware. The integrated navigation stack is evaluated and demonstrated in simulation. A hardware demonstration is also presented.