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Object detection and tracking for drones: A system design using dynamic visual SLAM
- 1 College of Design and Engineering, National University of Singapore, Singapore, Singapore
* Author to whom correspondence should be addressed.
Abstract
Drones can play a quite crucial role in many walks of life today. Enhancing the visual perception ability of drones is crucial to their intelligence level. Among them, it is necessary to focus on strengthening the detection, tracking and mapping capabilities of drones for dynamic objects. However, the existing visual SLAM systems carried by drones do not perform well in dynamic environments. This project designs a monocular visual SLAM system specifically for drones, aiming to achieve efficient three-dimensional mapping and target tracking, surpassing the limitations of simple static mapping and positioning. Besides, this project constructs a drone dynamic SLAM system developed on the ORB-SLAM3 structure, uses drone images to detect, track and map object motion models, and reconstructs environmental maps to obtain motion parameters with real physical scales. This project strives to optimize the input pre-processing module, improve the validity of data and output environmental maps and raster maps. The outcomes demonstrate the system's strong accuracy and adaptability in dynamic installation procedures.
Keywords
Visual simultaneous localization and mapping, Drones, Dynamic objects tracking.
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Cite this article
Wu,D. (2024). Object detection and tracking for drones: A system design using dynamic visual SLAM. Applied and Computational Engineering,81,71-82.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation
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