Simultaneous Localization and Mapping (SLAM) of Mobile Robots

A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: 15 October 2025 | Viewed by 61

Special Issue Editors

1. Zhejiang Energy Digital Technology Co., Ltd., Hangzhou 310012, China
2. School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
Interests: SLAM; localization & navigation; multi-sensor fusion; deep learning; computer vision; autonomous system

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Guest Editor
State Key Laboratory of Fluid Power, School of Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
Interests: SLAM; computer vision; path planning; autonomous system
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Special Issue Information

Dear Colleagues,

Simultaneous Localization and Mapping (SLAM) has long been a fundamental and challenging technology in enabling mobile robots to operate autonomously in unknown environments, where safety and precision are the vital issues for reliable and high-level autonomous applications. This Special Issue seeks to gather insights into state-of-the-art research and to promote the continuous progress of SLAM technology for mobile robots. Topics of interest for this Special Issue include, but are not limited to, the following:

  1. Advanced SLAM Algorithm Development: The improvement of existing algorithms to increase the accuracy and robustness of localization and mapping.
  2. AI and Machine Learning for SLAM: The integration of advanced AI and machine learning techniques with SLAM algorithms in dynamic and complex environments.
  3. Expansion of Application Scenarios: Applications of SLAM technology in new scenarios, such as environmental monitoring, autonomous delivery, and cultural heritage exploration.
  4. Cooperative SLAM (C-SLAM): Multi-robot SLAM system development, dealing with communication barriers, co-localization issues, and joint optimization problems to enable efficient and effective multi-robot navigation.
  5. Fast SLAM for Edge Deployment: Real-time SLAM on edge devices, Hardware–Software co-design optimization, efficient data processing technologies, and resource-constrained SLAM solutions.

Dr. Zhan Wang
Dr. Jin Wang
Guest Editors

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Keywords

  • localization and mapping
  • robotic navigation
  • autonomous system
  • AI-enhanced SLAM
  • vision inertial SLAM
  • multi-sensor fusion
  • mobile robot

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