Sensor Fusion for Autonomous Robotic Systems in Industrial and Service Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".
Deadline for manuscript submissions: 20 May 2026 | Viewed by 3
Special Issue Editors
Interests: robotics; system modeling and control; mechatronics; machine vision
Special Issues, Collections and Topics in MDPI journals
Interests: simultaneous localization and mapping; computer vision; robot; path-planning; pilotless aircraft; induction motor; energy efficiency; control system
Special Issue Information
Dear Colleagues,
The ability of robots to perceive and understand their surroundings is critical to achieving autonomy in real-world environments. As robotics increasingly expands into both industrial and service applications, the role of sensory information and sensor fusion has become more central than ever.
The continued advancement of sensing technologies—ranging from traditional 2D sensors to high-resolution 3D LiDARs, RGB-D cameras, event-based sensors, and mmWave radar—has greatly enriched the ways in which robots model and interpret their environments. In parallel, breakthroughs in artificial intelligence, including deep learning and foundation models such as Large Language Models (LLMs) and Vision-Language Models (VLMs), have introduced new possibilities for interpreting, combining, and reasoning over multimodal sensor data.
This Special Issue aims to gather original research and review papers that focus on the integration of multiple sensory modalities to enhance robotic perception, reasoning, and control. Topics of interest include, but are not limited to, the following:
- Sensor fusion for navigation, localization, mapping, and manipulation.
- The 2D/3D perception and multi-modal integration frameworks.
- AI-driven sensory processing, including deep learning and transformer-based models.
- Semantic-level fusion using LLMs, VLMs, or hybrid symbolic-learning systems.
- Real-time data fusion systems for dynamic and uncertain environments.
- Applications in smart manufacturing, autonomous logistics, healthcare, and field robotics.
- Challenges in sim-to-real transfer and robust deployment in real-world settings.
Prof. Dr. Chin-Sheng Chen
Guest Editor
Dr. Chia-Jen Lin
Guest Editor Assistant
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Keywords
- sensor fusion
- robotic autonomous perception
- AI-driven perception
- industrial robotics
- service robotics
- real-time data integration
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