Robot Path Planning in Regular Obstacle Environments with MATLAB Implementation

This documentation presents MATLAB source code designed for robot path planning in environments containing rule-based obstacles. The implementation enables autonomous navigation through obstacle-rich spaces while maintaining collision avoidance. The core algorithm computes optimal paths between specified start and end coordinates using heuristic search methods, potentially incorporating A* or Dijkstra's algorithm for efficient route optimization. Key features include modular obstacle definition systems allowing users to specify geometric constraints through parametric configurations. The code architecture supports dynamic obstacle integration through real-time position updating mechanisms. Path smoothing functions ensure trajectory feasibility using Bézier curves or spline interpolation techniques. The implementation provides visualization tools for simulating robot movement trajectories and obstacle interaction scenarios. Researchers can modify obstacle parameters through configuration files, adjusting dimensions, positions, and movement patterns. The codebase includes error handling for invalid path scenarios and collision detection algorithms using bounding-box or geometric intersection tests. This MATLAB solution serves as a foundational framework for developing advanced path planning systems, suitable for academic research and industrial applications in autonomous navigation systems. The object-oriented design permits straightforward extension to multi-robot scenarios or three-dimensional environments through additional module integration.