# Watch out! There may be a Human. Addressing Invisible Humans in Social Navigation

arXiv: https://arxiv.org/abs/2211.12216 · HTML: https://mlsanity.com/paper/2211.12216/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Nov 2022.

## Built on by (most cited first, 2 of 2)

- [Crowd-FM: Learned Optimal Selection of Conditional Flow Matching-generated Trajectories for Crowd Navigation](https://mlsanity.com/paper/2602.06698/) (2026)
- [Think When It Matters: Conditional VLM Reasoning for Social Navigation with RL Policies](https://mlsanity.com/paper/2607.10991/) (2026)

## Abstract (arXiv)

Current approaches in human-aware or social robot navigation address the humans that are visible to the robot. However, it is also important to address the possible emergences of humans to avoid shocks or surprises to humans and erratic behavior of the robot planner. In this paper, we propose a novel approach to detect and address these human emergences called `invisible humans'. We determine the places from which a human, currently not visible to the robot, can appear suddenly and then adapt the path and speed of the robot with the anticipation of potential collisions. This is done while still considering and adapting humans present in the robot's field of view. We also show how this detection can be exploited to identify and address the doorways or narrow passages. Finally, the effectiveness of the proposed methodology is shown through several simulated and real-world experiments.