Grid-Based Path Planning
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Resource Overview
Detailed Documentation
This project implements a grid-based path planning system that enables users to customize random obstacle placement for testing autonomous robot navigation capabilities. The implementation involves partitioning the environment into a grid structure and utilizing the A* search algorithm to compute optimal paths. This approach allows robots to dynamically avoid obstacles while successfully reaching their destination. The system provides valuable testing capabilities for autonomous navigation by simulating real-world random obstacle scenarios, effectively evaluating the robot's responsiveness and path planning efficiency. The A* algorithm implementation includes key functions for heuristic calculation, node expansion, and path reconstruction, ensuring efficient navigation through obstacle-rich environments. This functionality proves particularly useful for validating robotic systems' decision-making capabilities in unpredictable scenarios.
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