The AI Pathfinding Framework is a software system developed using C++ and OpenGL, designed to provide efficient pathfinding capabilities for various applications, such as game development or robotics simulations. This framework implements well-known pathfinding algorithms, including A* and Dijkstra's algorithm, allowing entities to navigate complex environments in an optimal manner.
By extending a maze creation and path planning demo, the project showcases enhanced AI capabilities for determining optimal routes within dynamically generated mazes. The integration of motion animation, transformations, and object management adds a significant layer of realism, allowing entities to interact smoothly within the virtual environment.
Pathfinding Algorithms: The framework incorporates two widely used pathfinding algorithms: A* and Dijkstra's algorithm. These algorithms help entities identify the most efficient path from a starting point to a destination while avoiding obstacles.
Maze Creation and Navigation: The framework generates dynamic mazes, creating unique environments for entities to navigate each time. This feature is ideal for testing and demonstrating the pathfinding capabilities of the system.
Hierarchical Object Management: The system leverages hierarchical object management for effective rendering and transformation of game objects. This allows for better organization, improved rendering performance, and more realistic animation.
Motion Animation and Transformations: The framework supports advanced transformations, such as rotation, scaling, and translation, providing smooth animations and realistic movement for entities navigating the maze.
OpenGL Visualization: The use of OpenGL for rendering enables high-quality graphics, making it easy to visualize the environment, the entities, and the paths being taken. This visualization is useful for both educational purposes and real-time demonstrations.