Asim Baig
Papers
2
Total Citations
12
H-Index
2
About
Asim Baig’s research sits at the intersection of robotic vision, autonomous navigation, and sensor fusion, with a focus on enabling mobile robots to perceive and interact with their environments in real time. His most cited work, “Calculating real world object dimensions from Kinect RGB-D image using dynamic resolution” (7 citations), tackles a fundamental challenge in robotic manipulation: accurately determining the physical size of objects from depth data. This capability is critical for tasks like path planning, collision avoidance, and workspace localization. In his earlier influential paper, “Real time localization of mobile robotic platform via fusion of Inertial and Visual Navigation System” (5 citations), Baig developed a hybrid approach combining inertial sensors with visual data to achieve robust, real-time positioning for ground and aerial robots. His contributions directly address the need for reliable localization in GPS-denied or dynamic environments. While his citation counts reflect a focused, early-career impact, Baig’s work demonstrates a clear trajectory toward practical, sensor-driven autonomy—laying groundwork for more adaptive and perceptive robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2