ai-based-maze-navigation-and-machine-learning

Designed and developed an AI-powered robotics solution for the HeroBot Dungeon environment by integrating supervised, unsupervised, and reinforcement learning techniques. The system was designed to perform image classification, entity clustering, and autonomous maze navigation, enabling intelligent perception and decision-making in a simulated robotic environment.

Implemented data preprocessing, feature extraction, and model training pipelines to improve the accuracy and efficiency of machine learning models. Evaluated multiple algorithms using performance metrics and comparative analysis to identify the most suitable approaches for robotic perception, navigation, and adaptive decision-making.

Integrated the optimized AI models into the robotic workflow to enhance  navigation performance.