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About

Shikha Singh is a robotics researcher specializing in nature-inspired optimization algorithms for autonomous navigation and motion planning. Her work focuses on enhancing the efficiency and adaptability of mobile robots through bio-inspired computational methods, particularly for path planning and steering control in complex environments. Singh’s most impactful contribution is the development of an optimized cuckoo search algorithm using tournament selection, which significantly improves robot path planning by reducing computational overhead and increasing solution accuracy—this work has garnered 27 citations. She has also applied the sunflower optimization algorithm to control the steering angle of two-wheeled Pioneer P3-DX robots in simulated V-REP environments, demonstrating practical motion planning solutions. Additionally, her research on minimizing computation time through an improvised cuckoo search algorithm addresses critical real-time performance challenges in robotics. Singh’s work bridges theoretical optimization techniques with tangible robotic applications, offering scalable solutions for autonomous systems. Her contributions are particularly relevant for researchers in swarm robotics, autonomous vehicles, and intelligent control systems, where efficient path planning remains a core challenge.