G. Yedukondalu
Papers
3
Total Citations
28
H-Index
3
About
G. Yedukondalu is a researcher at the forefront of industrial and agricultural robotics, specializing in robotic path planning, artificial intelligence, and machine vision. His work bridges the gap between theoretical algorithms and real-world automation, with a particular focus on enhancing the precision and autonomy of robotic systems. His most cited paper, "Robotic path planning and simulation by jacobian inverse for industrial applications" (2018, 21 citations), tackles the critical challenge of enabling serial robots—such as the KUKA KR5 Arc—to execute complex continuous-path tasks like welding and painting. By computing joint angles and simulating end-effector trajectories along sample curves, this work provides a foundational framework for improving industrial robotic dexterity. More recently, Yedukondalu has advanced into agricultural automation, applying Haar cascade techniques for tomato detection (2020) and developing AI algorithms for robotic harvesting (2025). These contributions aim to address labor shortages and reduce crop damage, showcasing his commitment to deploying intelligent robotics in high-impact, real-world settings. His growing citation record reflects a steady influence on both industrial manufacturing and precision agriculture.
Research Focus
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Top Papers
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