Adil Shahzad
Papers
4
Total Citations
80
H-Index
2
About
Adil Shahzad is a robotics and automation researcher whose work bridges intelligent control systems, computer vision, and practical engineering applications. His primary research areas include robotic manipulation, autonomous navigation, and smart agricultural systems. Shahzad’s most impactful contribution is his 2020 paper on a wirelessly controlled, Arduino-based smart irrigation system, which has garnered 52 citations—demonstrating significant interest in low-cost, renewable-energy-driven agricultural automation. In this work, he addressed the challenge of maximizing solar energy capture by developing a solar tracker integrated with robotic control, offering a sustainable solution for precision farming. His second most-cited paper (24 citations) presents a vision-based framework for path planning and object tracking using a 6-DOF robotic manipulator, enhancing industrial robot efficiency through machine vision and localization techniques. Shahzad has also contributed foundational work in robot kinematics, simulating the STEP SD 700 industrial robot’s trajectory following, and in monocular vision systems, developing a DLT-calibrated method for real-time RGB marker tracking. His research consistently focuses on making robotics more accessible, efficient, and applicable to real-world challenges, from factory floors to agricultural fields.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4