# NeRFoot: Robot-Footprint Estimation for Image-Based Visual Servoing

arXiv: https://arxiv.org/abs/2408.01251 · HTML: https://mlsanity.com/paper/2408.01251/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Aug 2024.

## Built on by (most cited first, 1 of 1)

- [Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval](https://mlsanity.com/paper/2411.04006/) (2024)

## Abstract (arXiv)

This paper investigates the utility of Neural Radiance Fields (NeRF) models in extending the regions of operation of a mobile robot, controlled by Image-Based Visual Servoing (IBVS) via static CCTV cameras. Using NeRF as a 3D-representation prior, the robot's footprint may be extrapolated geometrically and used to train a CNN-based network to extract it online from the robot's appearance alone. The resulting footprint results in a tighter bound than a robot-wide bounding box, allowing the robot's controller to prescribe more optimal trajectories and expand its safe operational floor area.