Features:

• Constraint-Based Painting Optimization: Assigns colors to walls while adhering to adjacency rules and paint availability. Computes the shortest traversal path using A* pathfinding and minimizes painting and travel time.
• 3D Visualization: Renders walls with their assigned colors and plots the robot’s traversal path.
• Dynamic Input Support: User-configurable wall definitions, constraints, and robot properties.
• Interactive 3D Visualization: Inspect and modify wall configurations dynamically.
• Multiple Rooms Support: Seamlessly handle complex environments with multiple connected rooms.

Setup:

Requirements:

• Python 3.8+
• Required Libraries: numpy, matplotlib, pyqt5

Usage:

1. Define Input:

Create a JSON input file (e.g., input.json) with the following structure:

          {
            "surfaces": [
              {"id": 1, "height": 3.0, "width": 4.0, "position": [0, 0, 0], "orientation": "vertical-x"},
              {"id": 2, "height": 3.0, "width": 4.0, "position": [4, 0, 0], "orientation": "vertical-y"}
            ],
            "colors": ["White", "Yellow", "Blue"],
            "time_per_meter": 2.0,
            "max_time": 300.0,
            "paint_availability": {"White": 15, "Yellow": 10, "Blue": 10},
            "adjacency_constraint": true,
            "min_colors": 2,
            "start_position": [0, 0, 0]
          }
        

2. Run the Solver:

python main.py

3. Output:

The solver provides:

• Assigned colors for walls.
• Total painting and travel time.
• Paint usage.
• 3D visualization of the environment.

Example Output:

=== Valid Solutions ===

Solution 1:
  - Total Time: 60.00 minutes
  - Colors Used: White, Yellow
  - Paint Usage: {'White': 12.0, 'Yellow': 12.0, 'Blue': 0.0}
  - Optimal Path: [(0, 0, 0), (4, 0, 0)]
----------------------------------------

GUI Screenshots:

Input GUI Screen	Output GUI Screen