Iqra Yaqoob
Papers
2
Total Citations
5
H-Index
2
About
Iqra Yaqoob is a robotics researcher specializing in autonomous navigation and sensor fusion, with a focus on real-time perception systems for mobile robots. Her work centers on integrating stereoscopic vision and multi-sensor data to enable robust, low-latency navigation in dynamic environments, particularly for warehouse automation. Her most-cited paper, "Performance evaluation of mobile stereonet for real time navigation in autonomous mobile robots" (2023), introduces a lightweight neural network architecture that processes stereo imagery on mobile platforms, achieving reliable obstacle detection and path planning without heavy computational overhead. This contribution is complemented by her study on sensor fusion, "Sensor Fusion-Based Approach for Real Time Navigation in Autonomous Mobile Robots Using Mobile Stereonet in Warehouse" (2023), which demonstrates how combining visual data with inertial and depth sensors improves localization accuracy in cluttered industrial settings. Though early in her career, Yaqoob’s work addresses critical challenges in deploying cost-effective autonomous systems, bridging the gap between academic research and practical warehouse logistics. Her publications reflect a growing impact in the field of mobile robotics, with potential applications in smart manufacturing and supply chain automation.
Research Focus
Key Achievements
Top Papers
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