Path Planning for Mobile Robots Using Genetic Algorithms

This documentation contains essential information about the original program implementation, which is highly suitable for graduation projects. The program simulates robot path planning utilizing genetic algorithm optimization techniques, featuring chromosome encoding for path representation, fitness functions evaluating path feasibility and length, and genetic operators including selection, crossover, and mutation. The system incorporates collision detection algorithms and environmental mapping modules to ensure realistic simulation scenarios. Designed with an intuitive GUI interface, the program enables users to visualize path evolution, adjust algorithm parameters (population size, mutation rates), and analyze performance metrics through graphical outputs. Complete with comprehensive documentation detailing code structure, API functions, and customization guidelines, this implementation provides a robust foundation for developing advanced path planning solutions with modular expandability for multi-objective optimization and dynamic environment adaptations.