An implementation of the A* algorithm for autonomous mobile robot navigation in partially unknown environments

Autonomous mobile robots require efficient and reliable path-planning algorithms to navigate in partially unknown environments. This work presents the implementation of the A* algorithm for path planning and obstacle avoidance in environments that are initially static but where the robot receives dynamic information during navigation. The algorithm dynamically updates the planned trajectory as new information about the environment becomes available, making it suitable for unstructured and evolving scenarios. The proposed system uses a 2D LiDAR sensor to detect obstacles and map an occupancy grid, enabling autonomous navigation for a differential drive mobile robot. The approach is validated through simulations and physical experiments. Results show that the A* algorithm improves navigation efficiency and adaptability compared to static path-planning methods.