Shivali Gupta
Papers
2
Total Citations
3
H-Index
1
About
Shivali Gupta is a rising researcher in autonomous robotics and computational intelligence, whose work focuses on solving one of the field’s most persistent challenges: real-time, adaptive path planning for mobile robots navigating dynamic environments. Her research centers on developing novel nature-inspired metaheuristic algorithms that balance exploration and exploitation to optimize robot trajectories while avoiding moving obstacles. In her highly cited 2025 paper, Gupta introduced the Black-Winged Kite Algorithm (BWKA), a bio-inspired optimization method that mimics the flight behavior of black-winged kites to achieve efficient path planning for four-wheeled mobile robots, earning 2 citations in its first year. She further advanced the field with her design of a Hybrid Slime Mold Algorithm, integrating the Slime Mold Algorithm with the Triangle Inequality Principle and Partition Method Strategy to enable real-time collision prevention in unpredictable settings. Though early in her career, Gupta’s work demonstrates significant impact by addressing the critical gap between theoretical optimization and practical autonomous navigation. Her innovative hybrid approaches are paving the way for more responsive, safer autonomous vehicles, marking her as a promising contributor to the next generation of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2