# Autonomous Reality Modelling for Cultural Heritage Sites employing cooperative quadrupedal robots and unmanned aerial vehicles

arXiv: https://arxiv.org/abs/2402.12794 · HTML: https://mlsanity.com/paper/2402.12794/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 25 references that are in the map.
- First posted on arXiv 20 Feb 2024.

## Builds on (most cited first, 4 of 4)

- [Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds](https://mlsanity.com/paper/2012.10002/) (2020)
- [A Reinforcement Learning Approach to the View Planning Problem](https://mlsanity.com/paper/1610.06204/) (2016)
- [Where to Explore Next? ExHistCNN for History-aware Autonomous 3D Exploration](https://mlsanity.com/paper/2011.14669/) (2020)
- [Predicting the Next Best View for 3D Mesh Refinement](https://mlsanity.com/paper/1805.06207/) (2018)

## Abstract (arXiv)

Nowadays, the use of advanced sensors, such as terrestrial 3D laser scanners, mobile LiDARs and Unmanned Aerial Vehicles (UAV) photogrammetric imaging, has become the prevalent practice for 3D Reality Modeling and digitization of large-scale monuments of Cultural Heritage (CH). In practice, this process is heavily related to the expertise of the surveying team, handling the laborious planning and time-consuming execution of the 3D mapping process that is tailored to the specific requirements and constraints of each site. To minimize human intervention, this paper introduces a novel methodology for autonomous 3D Reality Modeling for CH monuments by employing au-tonomous biomimetic quadrupedal robotic agents and UAVs equipped with the appropriate sensors. These autonomous robotic agents carry out the 3D RM process in a systematic and repeatable ap-proach. The outcomes of this automated process may find applications in digital twin platforms, facilitating secure monitoring and management of cultural heritage sites and spaces, in both indoor and outdoor environments.