Robot Path Planning and Obstacle Avoidance

This repository contains MATLAB source code for robot path planning and obstacle avoidance, designed to significantly contribute to research in robotic navigation systems. The codebase implements various fundamental algorithms and techniques including potential field methods, A* search algorithm, Dijkstra's algorithm, and Rapidly-exploring Random Trees (RRT). Each implementation includes configuration parameters for tuning obstacle detection thresholds, path optimization criteria, and motion planning constraints. The algorithms are structured with modular functions for clear separation of concerns: obstacle mapping using grid-based representations, cost calculation functions for path optimization, and collision detection modules using geometrical computations. Key functions feature detailed comments explaining mathematical formulations for distance calculations, heuristic functions for informed search algorithms, and interpolation methods for smooth trajectory generation. These implementations provide practical examples of how to handle real-world challenges in robotics, such as dynamic obstacle avoidance, multi-goal path planning, and computational efficiency optimization. Researchers can utilize this code as both educational reference material and as building blocks for developing more complex navigation systems, with clear entry points for modifying algorithm parameters and extending functionality. For researchers in robotics and autonomous systems, this MATLAB codebase serves as an excellent resource for understanding core concepts through executable examples, enabling faster prototyping and deeper investigation into advanced path planning methodologies. The code includes demonstration scripts that visualize algorithm performance metrics and comparative analysis between different planning approaches.