Mohammad Baziyad

Papers

Total Citations

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About

Mohammad Baziyad is an emerging researcher in the fields of robotics, mechatronics, and computer vision, with a focus on real-time object recognition and autonomous navigation. His most-cited work, "Real-Time Color Object Recognition and Navigation for QUARC QBOT2" (2017), demonstrates a practical integration of Microsoft Kinect-based vision systems with the QUARC QBOT2 ground robot—a platform combining mechatronics and robotics courseware. This contribution addresses a key challenge in robotics: enabling reliable, real-time color object detection for navigation in educational and applied settings. While his citation count is currently modest (3 citations), the work is foundational in demonstrating how low-cost, off-the-shelf sensors can be leveraged for robust robotic perception. Baziyad’s research bridges hardware and software, offering accessible solutions for robotics education and prototyping. His work is particularly notable for its emphasis on real-time performance, a critical requirement for autonomous systems. As the fields of educational robotics and vision-based navigation continue to grow, Baziyad’s contributions provide a stepping stone for students and researchers seeking to implement efficient object recognition on ground robots.