Nikhil Sethi
Papers
2
Total Citations
11
H-Index
2
About
Nikhil Sethi is a researcher focused on the intersection of evolutionary computation, multi-objective optimization, and autonomous drone systems. His primary contributions lie in developing advanced algorithms for drone flocking and swarm coordination, drawing inspiration from natural systems such as bird flocks and fish schools. In his most cited work, Sethi applies NSGA-II, a popular multi-objective genetic algorithm, combined with principal component analysis to optimize drone flocking behaviors, enabling efficient task execution in fields like defense, agriculture, and industrial automation. This work has garnered significant attention, with his top-cited paper accumulating 9 citations, reflecting its relevance to the growing field of autonomous aerial robotics. Sethi’s research addresses the challenge of enabling individual drones to coordinate locally while achieving global mission objectives, a key step toward practical, scalable drone swarms. His notable achievement includes demonstrating how evolutionary optimization can enhance the robustness and efficiency of multi-agent systems, making his work a valuable resource for students and researchers exploring swarm intelligence, autonomous systems, and bio-inspired engineering.
Research Focus
Key Achievements
Top Papers
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- 2