Mohammed Shafi Kundiladi
Papers
1
Total Citations
2
H-Index
1
About
Mohammed Shafi Kundiladi is a robotics researcher whose work focuses on the critical challenge of enabling safe, real-time motion planning for complex robotic systems. His primary research areas include redundant robot manipulators, inverse kinematics, and dynamic obstacle avoidance. Kundiladi’s major contribution lies in developing an adaptive meta-heuristic framework that allows redundant manipulators to navigate unpredictable environments while maintaining collision-free trajectories—a significant advancement over classical analytical and numerical methods. This framework addresses a core problem in robotics: finding optimal joint angles for a manipulator to reach a target point in 3D space without colliding with moving obstacles. His most-cited paper, “Adaptive Meta-heuristic Framework for Real-time Dynamic Obstacle Avoidance in Redundant Robot Manipulators” (2024), has already garnered 2 citations, demonstrating early impact in the field. By shifting from traditional approaches to adaptive, real-time solutions, Kundiladi’s work holds promise for applications in manufacturing, healthcare, and autonomous systems, where robots must operate safely alongside humans. His research represents a vital step toward more intelligent and responsive robotic systems.
Research Focus
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Top Papers
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