Advances in Environmental Sensing and Control for Mobile Robotics: Methods, Technologies, and Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".
Deadline for manuscript submissions: closed (15 October 2025) | Viewed by 9944
Editors
Interests: mathematical modeling; programming; electronics; telecommunications; robotics; sensors; control systems engineering
Special Issues, Collections and Topics in MDPI journals
Interests: electronic devices; measurement; sensitivity; sensors; physical quantities transducers; mobile robotic systems; remote control; mathematical model; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the impact of environmental factors on the performance and control of mobile robotic systems. As mobile robots are increasingly used in dynamic and unstructured environments, accurately sensing and responding to environmental conditions like temperature, humidity, wind, and obstacle characteristics is critical for reliable operation. This collection emphasizes advanced sensor technologies, adaptive control mechanisms, and machine learning approaches that improve sensor accuracy and system performance in such challenging environments.
The scope of this Special Issue covers innovations in environmental sensing, the development of models to account for environmental influences on sensor data, and the integration of IoT and AI to enhance environmental awareness in mobile robotics. It welcomes contributions on both hardware and software solutions, experimental studies, and real-world applications across various industries including agriculture, healthcare, autonomous vehicles, and disaster response.
The purpose of this Special Issue is to bridge the knowledge gap by presenting novel research on how environmental factors affect robotic sensors and systems. It aims to push the boundaries of sensor calibration, environmental modeling, and adaptive control, offering solutions that supplement the existing literature. This collection will provide fresh insights into overcoming environmental challenges, thus supporting the next generation of mobile robotic systems that operate effectively in unpredictable environments.
Dr. Serhii Baraban
Prof. Dr. Andriy Semenov
Guest Editors
Manuscript Submission Information
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Keywords
- mobile robotics
- environmental sensors
- ultrasonic rangefinders
- technical vision systems
- sensor accuracy
- atmospheric conditions
- machine learning in robotics
- sensor calibration
- obstacle detection
- neural networks in robotics
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