VRExplorer: An Efficient View-Region based Autonomous Exploration Method in Unknown Environments for UAV

Autonomous exploration plays a crucial role in robotics applications like rescue and scene reconstruction. This work addresses the challenges of autonomous exploration in intricate unknown environments by presenting a novel UAV autonomous exploration method based on a new concept of the view-region. Our proposed approach leverages the view-region to replace the conventional viewpoint generation and selection process, streamlining the planning process for exploration. Simultaneously, we model the problem of maximizing frontier coverage within the field of view during exploration, and jointly optimize it with the exploration path optimization problem. This approach ensures exploration path safety and effectiveness while being aggressive. Additionally, a gimbal is incorporated beneath the camera, with an associated optimization problem designed to minimize UAV self-rotation and enhance exploration efficiency. Simulations and real-world experiments demonstrate that the proposed method outperforms existing state-of-the-art methods in terms of runtime and distance traveled.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802710
Citations
4
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
5.20

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article

VRExplorer: An Efficient View-Region based Autonomous Exploration Method in Unknown Environments for UAV

Mingxin Wei, Lanxiang Zheng, Hui Cheng, Kai Xu
4 citations
Robotics and Sensor-Based Localization
5.20
article

VRExplorer: An Efficient View-Region based Autonomous Exploration Method in Unknown Environments for UAV

Mingxin Wei, Lanxiang Zheng, Hui Cheng, Kai Xu
article en
4 citations

Abstract

Autonomous exploration plays a crucial role in robotics applications like rescue and scene reconstruction. This work addresses the challenges of autonomous exploration in intricate unknown environments by presenting a novel UAV autonomous exploration method based on a new concept of the view-region. Our proposed approach leverages the view-region to replace the conventional viewpoint generation and selection process, streamlining the planning process for exploration. Simultaneously, we model the problem of maximizing frontier coverage within the field of view during exploration, and jointly optimize it with the exploration path optimization problem. This approach ensures exploration path safety and effectiveness while being aggressive. Additionally, a gimbal is incorporated beneath the camera, with an associated optimization problem designed to minimize UAV self-rotation and enhance exploration efficiency. Simulations and real-world experiments demonstrate that the proposed method outperforms existing state-of-the-art methods in terms of runtime and distance traveled.

Sun Yat-sen University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 5%
Robotics and Sensor-Based Localization
5.20
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