Implementation of Grid-Based Path Planning for Robots

In this project, we utilize MATLAB to implement grid-based path planning for robots. This path planning methodology represents a widely adopted approach that discretizes the operational environment into a series of grid cells to compute optimal robot trajectories while ensuring safe obstacle avoidance. Our implementation includes practical routines featuring core functions such as grid map initialization, neighbor cell exploration, and cost calculation algorithms. The code structure incorporates essential path planning components including distance heuristic functions, obstacle detection mechanisms, and backtracking procedures for path reconstruction. We have developed comparative analysis modules that enable performance evaluation against alternative path planning algorithms like A*, Dijkstra, and potential field methods to determine the most suitable approach for specific applications. Through grid-based path planning implementation, users can ensure enhanced safety and reliability for robotic navigation in complex environments, with configurable parameters for grid resolution, obstacle padding, and optimization criteria.