Guoqiang Ma

Papers

Total Citations

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About

Guoqiang Ma’s research lies at the intersection of robotics, sensor fusion, and autonomous navigation, with a particular emphasis on SLAM (Simultaneous Localization and Mapping) systems. His most cited work, “Research on SLAM Intelligent Robot Based on Visual Laser Fusion” (2024), introduces a novel integration of lidar and depth camera data within a ROS framework, using an STM32 microcontroller for motion control and a Raspberry Pi for higher-level processing. This design enables intelligent robots to autonomously map unknown environments while maintaining precise self-localization—a critical capability for applications in search-and-rescue, industrial automation, and service robotics. Although early in its citation trajectory (2 citations), the paper reflects Ma’s forward-looking approach to combining cost-effective hardware with robust algorithms. His contributions advance the field by demonstrating how visual-laser fusion can overcome the limitations of single-sensor SLAM, improving accuracy and reliability in real-world settings. For students and researchers exploring autonomous systems, Ma’s work offers a practical blueprint for building scalable, sensor-rich robots that bridge the gap between theoretical SLAM methods and deployable solutions.