Papers
3
Total Citations
29
H-Index
2
About
Weimin Shi is a researcher at the forefront of intelligent autonomous systems, with a primary focus on computer vision, environmental perception, and path planning for robotics. Their work is distinguished by a deep integration of visual SLAM algorithms and object detection techniques, directly addressing the critical challenges of energy efficiency and dynamic obstacle avoidance in autonomous platforms. Shi’s most impactful contribution, a comprehensive 2024 survey on computer vision and visual SLAM for energy-efficient autonomous systems, has already garnered 22 citations, reflecting its importance as a foundational resource for researchers in driverless vehicles and automated production. Further demonstrating their applied expertise, Shi developed a novel fusion algorithm, NRBO-DWA, for path planning in yarn-changing robots, achieving more efficient search processes and robust dynamic obstacle avoidance—a solution published in 2024. Their work consistently bridges the gap between theoretical computer vision and practical robotic navigation, with additional surveys on sensing capabilities for driverless vehicles. By tackling both algorithmic efficiency and real-world implementation, Weimin Shi is making notable strides toward more intelligent, autonomous, and energy-conscious robotic systems.
Research Focus
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Top Papers
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