Karthika Sundaran
Papers
8
Total Citations
105
H-Index
4
About
Karthika Sundaran is a robotics researcher specializing in trajectory planning and autonomous navigation for wheeled mobile robots and medical robotic systems. Her work focuses on developing enhanced sampling-based algorithms that enable robots to generate smooth, obstacle-free paths in complex environments. Sundaran's major contributions include the creation of an Enhanced Artificial Potential Field (E-APF) method, which improves upon traditional approaches by generating more efficient trajectories for mobile robot navigation. She has also pioneered the integration of spline techniques with Probabilistic Roadmaps (PRM) and bidirectional Rapidly-exploring Random Tree star (RRT*) algorithms to produce smoother, more physically feasible paths. Her most cited work, "Obstacle Avoidance and Navigation Planning of a Wheeled Mobile Robot using Amended Artificial Potential Field Method" (2018), has garnered 67 citations, demonstrating significant impact in the field. Sundaran has extended her trajectory planning expertise to medical applications, including robotic surgery and pliable needle insertion, exploring how sampling-based algorithms can meet the physical constraints of human tissue. Her research portfolio, spanning optimization techniques like artificial bee colony and genetic algorithms, showcases a comprehensive approach to solving real-world navigation challenges in both industrial and surgical robotics.
Research Focus
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Top Papers
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