# Developing a Flying Explorer for Autonomous Digital Modelling in Wild Unknowns

**Authors:** Naizhong Zhang, Yaoqiang Pan, Yangwen Jin, Peiqi Jin, Kewei Hu, Xiao Huang, Hanwen Kang

PMC · DOI: 10.3390/s24031021 · Sensors (Basel, Switzerland) · 2024-02-05

## TL;DR

The paper introduces a flying robot system for autonomous exploration and digital modeling in unknown environments, using advanced path planning and odometry techniques.

## Contribution

The novel contribution is a minimum cost-based exploration approach with dynamic objectives for autonomous digital modeling in unknown environments.

## Key findings

- The proposed method successfully completes autonomous exploration and modeling in complex indoor and outdoor scenes.
- The system demonstrates robustness in handling dynamic target changes and varying odometry types.
- Experiments validate the efficiency and consistency of the approach in unknown environments.

## Abstract

Digital modelling stands as a pivotal step in the realm of Digital Twinning. The future trend of Digital Twinning involves automated exploration and environmental modelling in complex scenes. In our study, we propose an innovative solution for robot odometry, path planning, and exploration in unknown outdoor environments, with a focus on Digital modelling. The approach uses a minimum cost formulation with pseudo-randomly generated objectives, integrating multi-path planning and evaluation, with emphasis on full coverage of unknown maps based on feasible boundaries of interest. The approach allows for dynamic changes to expected targets and behaviours. The evaluation is conducted on a robotic platform with a lightweight 3D LiDAR sensor model. The robustness of different types of odometry is compared, and the impact of parameters on motion planning is explored. The consistency and efficiency of exploring completely unknown areas are assessed in both indoor and outdoor scenarios. The experiment shows that the method proposed in this article can complete autonomous exploration and environmental modelling tasks in complex indoor and outdoor scenes. Finally, the study concludes by summarizing the reasons for exploration failures and outlining future focuses in this domain.

## Full-text entities

- **Genes:** FASTK (Fas activated serine/threonine kinase) [NCBI Gene 10922] {aka FAST}
- **Diseases:** injury to people or property (MESH:C000719191), DM (MESH:D004195)
- **Chemicals:** carbon fibre (MESH:D000077482), LiDAR (-)

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/PMC10857124/full.md

## References

30 references — full list in the complete paper: https://tomesphere.com/paper/PMC10857124/full.md

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Source: https://tomesphere.com/paper/PMC10857124