Advanced Sensing for Intelligent Robot Localization and Navigation
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".
Deadline for manuscript submissions: 31 October 2026
Special Issue Editors
Interests: SLAM; place recognition; multiple modal perception; intelligent interaction; human–machine collaboration; embodied intelligence systems
Interests: robot motion planning; robot control; human–robot collaboration; intelligent information processing; intelligent control
Interests: multi-sensor fusion; robot navigation; autonomous unmanned system applications; sensing technologies; robot localization
Special Issue Information
Dear Colleagues,
Intelligent robots are increasingly expected to operate safely and efficiently in complex, dynamic, and unstructured environments. A core challenge in this field is accurate localization and navigation, which heavily rely on advanced sensing technologies. With the rapid progress in sensing hardware and algorithms, robots can now leverage diverse modalities such as LiDAR, vision, inertial sensors, GNSS, radar, and even Wi-Fi signals to achieve robust perception and precise localization.
This Special Issue aims to bring together researchers and practitioners from academia and industry to explore innovative sensing technologies and their applications in intelligent robot navigation and positioning. It aligns with Sensors’ focus on novel sensing systems, data fusion and intelligent processing, and advanced localization and navigation applications. We welcome submissions employing state-of-the-art approaches and novel frameworks, addressing topics including, but not limited to, the following:
- Multi-sensor fusion for robot localization and navigation;
- Advanced LiDAR, vision, radar, and inertial sensing technologies;
- 3D dense mapping, semantic mapping, and scene graph mapping for dynamic environment navigation and localization;
- Learning-based methods for perception, navigation, and localization;
- Robust navigation in GPS-denied or challenging environments;
- Information-theoretic and uncertainty-aware sensing strategies;
- Collaborative perception and localization for multi-robot systems;
- Long-term autonomy and adaption to environmental change;
- Applications in autonomous vehicles, drones, service robots, and planetary rovers
Prof. Dr. Hongshan Yu
Prof. Dr. Jinzhu Peng
Dr. Jiang Zhu
Dr. Zhiwen Zeng
Guest Editors
Manuscript Submission Information
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Keywords
- multi-sensor fusion for robot localization and navigation
- advanced LiDAR, vision, radar, and inertial sensing technologies
- 3D dense mapping, semantic mapping, and scene graph mapping for dynamic environment navigation and localization
- learning-based methods for perception, navigation, and localization
- robust navigation in GPS-denied or challenging environments
- information-theoretic and uncertainty-aware sensing strategies
- collaborative perception and localization for multi-robot systems
- long-term autonomy and adaption to environmental change
- applications in autonomous vehicles, drones, service robots, and planetary rovers
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