(untitled) (Journal of Computational Intelligence and Robotics, 2024)
Evolutionary optimization techniques have shown promise in solving complex problems in various domains. In this paper, we explore the application of evolutionary optimization for robot path planning in dynamic environments. We review existing literature on evolutionary algorithms and their adaptation for path planning. Our study focuses on how these techniques can address challenges such as dynamic obstacles, real-time decision making, and efficient path computation. We evaluate the performance of evolutionary algorithms against traditional methods and discuss their advantages and limitations. Through simulations and case studies, we demonstrate the effectiveness of evolutionary optimization for robot path planning in dynamic environments.