Vivek Kumar Sharma

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About

Vivek Kumar Sharma is a researcher in computational intelligence and robotics, with a primary focus on optimization algorithms and autonomous navigation. His work centers on applying evolutionary computation techniques—particularly differential evolution—to solve complex real-world problems in robot path planning. Sharma’s major contributions include the development of bio-inspired optimization methods, such as the Peregrine preying pattern based differential evolution algorithm, which mimics the hunting strategy of peregrine falcons to enhance the efficiency and robustness of path planning in dynamic environments. His most-cited papers, "Peregrine preying pattern based differential evolution for robot path planning" (2020, 12 citations) and "Robot Path Planning Using Differential Evolution" (2020, 11 citations), demonstrate his ability to bridge theoretical optimization with practical robotic applications. These works have garnered attention for their novel integration of natural predator-prey dynamics into evolutionary algorithms, offering more adaptive and collision-free navigation solutions. Sharma’s research is particularly impactful for students and engineers seeking efficient, nature-inspired approaches to autonomous systems, and his work continues to influence the development of smarter, more responsive robotic platforms.