Papers
1
Total Citations
6
H-Index
1
About
Aquib Rashid is a researcher focused on advancing perception and calibration techniques for robotic systems, with a particular emphasis on integrating LiDAR, cameras, and industrial robots. His most cited work, "Open-Box Target for Extrinsic Calibration of LiDAR, Camera and Industrial Robot" (2020), addresses a critical challenge in human-robot collaboration: achieving accurate, low-cost extrinsic calibration between sensors and robotic arms. By introducing an efficient calibration method using an open-box target, Rashid’s contribution enables safer and more reliable perception for applications ranging from manufacturing to autonomous systems. This work has garnered significant attention, accumulating 6 citations and underscoring its practical value in the robotics community. Rashid’s research sits at the intersection of sensor fusion, calibration, and industrial automation, demonstrating a commitment to making robotic systems more accessible and robust. His efforts are particularly notable for reducing the complexity and cost of sensor integration, a key barrier in deploying collaborative robots. For students and researchers, Rashid’s work offers a clear example of how targeted methodological innovations can have a tangible impact on real-world robotics, paving the way for more intuitive and efficient human-robot interaction.
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Top Papers
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