Multi-sensor Integration for Navigation and Environmental Sensing
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".
Deadline for manuscript submissions: 20 November 2024 | Viewed by 2391
Special Issue Editor
Special Issue Information
Dear Colleagues,
The evolution of navigation and perception sensor technologies in recent years has opened the door for developing low-cost autonomous systems, including autonomous vehicles and small unmanned aerial systems (UAS). Such systems can potentially be used in many critical applications, both outdoor and indoor. Outdoor applications include mobile mapping, disaster monitoring, and precision agriculture, to name a few. Indoor applications, on the other hand, include manufacturing and distribution facilities, the health sector, and public safety, among others. The use of autonomous systems in these critical applications, however, requires continuous high-accuracy positioning and attitude (pose) information of the platform, along with environmental sensing and object classification. In addition, some use cases of market verticals such as smart manufacturing, warehousing and supply chains, and transportation require seamless indoor/outdoor operational capabilities.
MDPI is planning to publish a special issue of its Sensors journal on multi-sensor integration for navigation and environmental sensing. This issue will focus on next-generation algorithms and estimation methodologies for a low-cost autonomous multi-sensor integrated system for precise real-time seamless indoor/outdoor navigation and environmental sensing. Topics of particular interest include but are not limited to:
- Multi-sensor integration for mobile and UAS mapping;
- Integration of monocular/stereo/event camera-based visual-inertial odometry (VIO)/simultaneous localization and mapping (SLAM);
- Integration of solid-state LiDAR-inertial odometry (LIO)/SLAM;
- Real-time autonomous tightly-coupled GNSS/LVIO integration for challenging GNSS signal, weather, and illumination conditions;
- Integration of fifth-generation (5G) millimeter wave (mmWave)/LVIO for GNSS-denied environments;
- Deep-learning-based algorithms for classification and semantic segmentation of LiDAR/Photogrammetric point cloud of the surrounding environment.
Prof. Dr. Ahmed El-Rabbany
Guest Editor
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