Abstract

The paper proposes the development and construction of a bipedal walking mechanism with a focus on planar locomotion, incorporating advanced Artificial Intelligence (AI) concepts. The two-legged walking robot employs Machine Learning (ML) for Gait Optimization to adapt its walking pattern based on factors like speed, terrain and energy efficiency. Integration of multiple sensors with AI for improved balance, utilizing predictive analytics for obstacle avoidance and collision prevention. The study includes a GUI developed using Python to facilitate user interaction. A comprehensive literature survey on obstacle avoidance contributes to the understanding of existing approaches. In this paper, we explore the intersection of robotics and AI, discussing key technologies, challenges, and potential future developments. ML algorithms and computer vision play pivotal roles in enabling robots to acquire and apply knowledge etc..