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

arXiv: https://arxiv.org/abs/2104.05933 · HTML: https://mlsanity.com/paper/2104.05933/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Apr 2021.

## Built on by (most cited first, 4 of 4)

- [A Survey on Human-aware Robot Navigation](https://mlsanity.com/paper/2106.11650/) (2021)
- [Towards Deviation-Robust Agent Navigation via Perturbation-Aware Contrastive Learning](https://mlsanity.com/paper/2403.05770/) (2024)
- [CANVAS: Commonsense-Aware Navigation System for Intuitive Human-Robot Interaction](https://mlsanity.com/paper/2410.01273/) (2024)
- [Urban Risk-Aware Navigation via VQA-Based Event Maps for People with Low Vision](https://mlsanity.com/paper/2605.11782/) (2026)

## Abstract (arXiv)

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 textitgroup 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.