Toward Integrating Semantic-aware Path Planning and Reliable Localization for UAV Operations

Thanh Nguyen Canh

Huy-Hoang Ngo

Xiem HoangVan

Nak Young Chong

School of Information Science, JAIST, Japan
VNU University of Engineering and Technology, Vietnam
ICCAS, 2024.

[Paper]

Localization is one of the most crucial tasks for Unmanned Aerial Vehicle systems (UAVs) directly impacting overall performance, which can be achieved with various sensors and applied to numerous tasks related to search and rescue operations, object tracking, construction, etc. However, due to the negative effects of challenging environments, UAVs may lose signals for localization. In this paper, we present an effective path-planning system leveraging semantic segmentation information to navigate around texture-less and problematic areas like lakes, oceans, and high-rise buildings using a monocular camera. We introduce a real-time semantic segmentation architecture and a novel keyframe decision pipeline to optimize image inputs based on pixel distribution, reducing processing time. A hierarchical planner based on the Dynamic Window Approach (DWA) algorithm, integrated with a cost map, is designed to facilitate efficient path planning. The system is implemented in a photo-realistic simulation environment using Unity, aligning with segmentation model parameters. Comprehensive qualitative and quantitative evaluations validate the effectiveness of our approach, showing significant improvements in the reliability and efficiency of UAV localization in challenging environments.

Paper

Thanh Nguyen Canh, Huy-Hoang Ngo, Xiem HoangVan, Nak Young Chong

Toward Integrating Semantic-aware Path Planning and Reliable Localization for UAV Operations

ICCAS 2024.

[pdf]

Overview and Results

Overview

Overall architecture of our proposed system: The system is composed of three main units: Key Frame Decision Module, Semantic Segmentation Module, and Integration for Semantic Information and Path Planning.

Experiments

Flight trajectories recorded: the white trajectory represents Semantic-aware DWA, the green and red trajectories represent DWA.

Quantitative comparison for flight performance (Flight Distance (F-D), Unreliable Distance (U-D) meter).

Citation

1. Canh T. N., Ngo H-H, HoangVan X., Chong A.Y. Toward Integrating Semantic-aware Path Planning and Reliable Localization for UAV Operations. International Conference on Control, Automation, and Systems (ICCAS), 2024.

@inproceedings{canh2024s3m, 
                                  

                                    author    = {Canh, Thanh Nguyen and Ngo, Huy-Hoang and HoangVan, Xiem and Chong, Nak Young}, 
                                  

                                    title     = {{Toward Integrating Semantic-aware Path Planning and Reliable Localization for UAV Operations}}, 
                                  

                                    booktitle = {2024 24th International Conference on Control, Automation and Systems (ICCAS)}, 
                                  

                                    year      = {2024}, 
                                  

                                    pages     = {719--724},
                                  

                                  organization= {IEEE}, 
                                  

                                    DOI       = {10.23919/ICCAS63016.2024.10773342}
                                  

                                }

Acknowledgements

We gratefully acknowledge support fromthe Asian Office of Aerospace Research and Development under Grant/Cooperative Agreement Award No. FA2386-22-1-4042.
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