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September 10, 2025電腦學刊

Enhanced Multi-Sensor Fusion for SLAM in Unstructured Environments: A Robust Localization and Mapping Framework for Mobile Robots

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Authors

HWHan WangYLYupeng LiJHJonghui Han

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Overview

This framework improves localization and mapping accuracy in mobile robots using multi-sensor data, suggesting higher adaptability to environmental changes.

Key Points

  • Localization error is significantly reduced using a novel adaptive multi-sensor SLAM framework, enhancing precision.
  • Experimental results demonstrate improved loop closure accuracy compared to existing state-of-the-art SLAM frameworks, with real-time processing.
  • The integration of lidar, vision, and inertial data via factor graph optimization supports robust performance in unstructured environments.
  • Adaptive fusion strategies adjust sensor contributions dynamically, highlighting potential for future applications in multi-robot collaboration.

Cite This Study

Wang et al. (2025) studied this question.

synapsesocial.com/papers/68c1d97154b1d3bfb60fad3chttps://doi.org/10.63367/199115992025083604015
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