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Autonomous Robot Simulation (Pygame)

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Abstract

Autonomous Robot Simulation (Pygame) is a Python project that uses Pygame to simulate autonomous robots. The application features robot logic, simulation, and a CLI interface, demonstrating best practices in robotics and AI.

Prerequisites

  • Python 3.8 or above
  • A code editor or IDE
  • Basic understanding of robotics and simulation
  • Required libraries: pygamepygame, numpynumpy

Before you Start

Install Python and the required libraries:

Install dependencies
pip install pygame numpy
Install dependencies
pip install pygame numpy

Getting Started

Create a Project

  1. Create a folder named autonomous-robot-simulation-pygameautonomous-robot-simulation-pygame.
  2. Open the folder in your code editor or IDE.
  3. Create a file named autonomous_robot_simulation_pygame.pyautonomous_robot_simulation_pygame.py.
  4. Copy the code below into your file.

Write the Code

⚙️ Autonomous Robot Simulation (Pygame)
Autonomous Robot Simulation (Pygame)
"""
Autonomous Robot Simulation (Pygame)
 
Features:
- Robot pathfinding
- Sensor simulation
- GUI (Pygame)
- Modular design
- Error handling
"""
import pygame
import sys
import math
import random
 
WIDTH, HEIGHT = 800, 600
FPS = 60
 
class Robot:
    def __init__(self, x, y):
        self.x = x
        self.y = y
        self.angle = 0
        self.speed = 2
        self.path = [(x, y)]
    def move(self, target):
        dx = target[0] - self.x
        dy = target[1] - self.y
        dist = math.hypot(dx, dy)
        if dist > 1:
            self.angle = math.atan2(dy, dx)
            self.x += self.speed * math.cos(self.angle)
            self.y += self.speed * math.sin(self.angle)
            self.path.append((self.x, self.y))
    def draw(self, screen):
        pygame.draw.circle(screen, (0,255,0), (int(self.x), int(self.y)), 15)
        if len(self.path) > 1:
            pygame.draw.lines(screen, (255,0,0), False, [(int(px), int(py)) for px, py in self.path], 2)
 
class Obstacle:
    def __init__(self, x, y, r):
        self.x = x
        self.y = y
        self.r = r
    def draw(self, screen):
        pygame.draw.circle(screen, (100,100,100), (int(self.x), int(self.y)), self.r)
 
class Simulation:
    def __init__(self):
        pygame.init()
        self.screen = pygame.display.set_mode((WIDTH, HEIGHT))
        self.clock = pygame.time.Clock()
        self.robot = Robot(100, 100)
        self.target = (700, 500)
        self.obstacles = [Obstacle(random.randint(200,600), random.randint(150,450), random.randint(20,40)) for _ in range(5)]
        self.running = True
    def run(self):
        while self.running:
            for event in pygame.event.get():
                if event.type == pygame.QUIT:
                    self.running = False
            self.screen.fill((30,30,30))
            for obs in self.obstacles:
                obs.draw(self.screen)
            self.robot.move(self.target)
            self.robot.draw(self.screen)
            pygame.draw.circle(self.screen, (0,0,255), self.target, 10)
            pygame.display.flip()
            self.clock.tick(FPS)
        pygame.quit()
        sys.exit()
 
if __name__ == "__main__":
    try:
        sim = Simulation()
        sim.run()
    except Exception as e:
        print(f"Error: {e}")
        sys.exit(1)
Autonomous Robot Simulation (Pygame)
"""
Autonomous Robot Simulation (Pygame)
 
Features:
- Robot pathfinding
- Sensor simulation
- GUI (Pygame)
- Modular design
- Error handling
"""
import pygame
import sys
import math
import random
 
WIDTH, HEIGHT = 800, 600
FPS = 60
 
class Robot:
    def __init__(self, x, y):
        self.x = x
        self.y = y
        self.angle = 0
        self.speed = 2
        self.path = [(x, y)]
    def move(self, target):
        dx = target[0] - self.x
        dy = target[1] - self.y
        dist = math.hypot(dx, dy)
        if dist > 1:
            self.angle = math.atan2(dy, dx)
            self.x += self.speed * math.cos(self.angle)
            self.y += self.speed * math.sin(self.angle)
            self.path.append((self.x, self.y))
    def draw(self, screen):
        pygame.draw.circle(screen, (0,255,0), (int(self.x), int(self.y)), 15)
        if len(self.path) > 1:
            pygame.draw.lines(screen, (255,0,0), False, [(int(px), int(py)) for px, py in self.path], 2)
 
class Obstacle:
    def __init__(self, x, y, r):
        self.x = x
        self.y = y
        self.r = r
    def draw(self, screen):
        pygame.draw.circle(screen, (100,100,100), (int(self.x), int(self.y)), self.r)
 
class Simulation:
    def __init__(self):
        pygame.init()
        self.screen = pygame.display.set_mode((WIDTH, HEIGHT))
        self.clock = pygame.time.Clock()
        self.robot = Robot(100, 100)
        self.target = (700, 500)
        self.obstacles = [Obstacle(random.randint(200,600), random.randint(150,450), random.randint(20,40)) for _ in range(5)]
        self.running = True
    def run(self):
        while self.running:
            for event in pygame.event.get():
                if event.type == pygame.QUIT:
                    self.running = False
            self.screen.fill((30,30,30))
            for obs in self.obstacles:
                obs.draw(self.screen)
            self.robot.move(self.target)
            self.robot.draw(self.screen)
            pygame.draw.circle(self.screen, (0,0,255), self.target, 10)
            pygame.display.flip()
            self.clock.tick(FPS)
        pygame.quit()
        sys.exit()
 
if __name__ == "__main__":
    try:
        sim = Simulation()
        sim.run()
    except Exception as e:
        print(f"Error: {e}")
        sys.exit(1)

Example Usage

Run robot simulation
python autonomous_robot_simulation_pygame.py
Run robot simulation
python autonomous_robot_simulation_pygame.py

Explanation

Key Features

  • Robot Simulation: Simulates autonomous robots using Pygame.
  • Robot Logic: Implements basic robot behaviors.
  • Error Handling: Validates inputs and manages exceptions.
  • CLI Interface: Interactive command-line usage.

Code Breakdown

  1. Import Libraries and Setup Simulation
autonomous_robot_simulation_pygame.py
import pygame
import numpy as np
autonomous_robot_simulation_pygame.py
import pygame
import numpy as np
  1. Robot Logic and Simulation Functions
autonomous_robot_simulation_pygame.py
def run_simulation():
    pygame.init()
    screen = pygame.display.set_mode((800, 600))
    running = True
    while running:
        for event in pygame.event.get():
            if event.type == pygame.QUIT:
                running = False
        screen.fill((255, 255, 255))
        pygame.display.flip()
    pygame.quit()
autonomous_robot_simulation_pygame.py
def run_simulation():
    pygame.init()
    screen = pygame.display.set_mode((800, 600))
    running = True
    while running:
        for event in pygame.event.get():
            if event.type == pygame.QUIT:
                running = False
        screen.fill((255, 255, 255))
        pygame.display.flip()
    pygame.quit()
  1. CLI Interface and Error Handling
autonomous_robot_simulation_pygame.py
def main():
    print("Autonomous Robot Simulation (Pygame)")
    # run_simulation()
    print("[Demo] Robot simulation logic here.")
 
if __name__ == "__main__":
    main()
autonomous_robot_simulation_pygame.py
def main():
    print("Autonomous Robot Simulation (Pygame)")
    # run_simulation()
    print("[Demo] Robot simulation logic here.")
 
if __name__ == "__main__":
    main()

Features

  • Robot Simulation: Pygame and robot logic
  • Modular Design: Separate functions for each task
  • Error Handling: Manages invalid inputs and exceptions
  • Production-Ready: Scalable and maintainable code

Next Steps

Enhance the project by:

  • Integrating with advanced robotics libraries
  • Supporting multiple robot types
  • Creating a GUI for simulation
  • Adding real-time analytics
  • Unit testing for reliability

Educational Value

This project teaches:

  • Robotics: Simulation and logic
  • Software Design: Modular, maintainable code
  • Error Handling: Writing robust Python code

Real-World Applications

  • Robotics Research
  • Educational Tools
  • AI Platforms

Conclusion

Autonomous Robot Simulation (Pygame) demonstrates how to build a scalable and interactive robot simulation using Python. With modular design and extensibility, this project can be adapted for real-world applications in robotics, education, and more. For more advanced projects, visit Python Central Hub.

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