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Python simulation of a robot navigating toward a target while avoiding dynamic obstacles. Utilizing the Pure Pursuit algorithm for path following and the Vector Field Histogram (VFH) for real-time obstacle avoidance, the robot intelligently adjusts its course to reach the target safely. Visualizations include the robot’s path

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VFH for Collision Avoidance

Screenshot 2024-11-02 163145

Robot Navigation Simulation with Pure Pursuit and Vector Field Histogram

This project simulates a robot navigating towards a target while avoiding dynamic obstacles using the Pure Pursuit Method for path following and Vector Field Histogram (VFH) for obstacle avoidance.


Overview

This simulation demonstrates:

  1. Pure Pursuit Path Following
    The robot calculates the angle toward the target and adjusts its orientation accordingly to follow the path.

  2. Vector Field Histogram (VFH) Obstacle Avoidance
    The robot scans its environment to detect nearby obstacles, generating a histogram of distances within its field of view. When obstacles are detected within a certain threshold distance, the robot adjusts its orientation to avoid them.

  3. Dynamic Obstacles
    Obstacles move randomly, adding complexity to the robot's navigation task.


Features

  • Dynamic Targeting: The robot continuously re-orients toward a target position.
  • Obstacle Avoidance: Upon detecting obstacles, the robot selects a safe angle to prevent collisions.
  • Real-time Plotting: The simulation visually represents the robot, target, obstacles, and sensor beams.
  • Polar Histogram Display: An inset plot shows the polar histogram of obstacle distances.

About

Python simulation of a robot navigating toward a target while avoiding dynamic obstacles. Utilizing the Pure Pursuit algorithm for path following and the Vector Field Histogram (VFH) for real-time obstacle avoidance, the robot intelligently adjusts its course to reach the target safely. Visualizations include the robot’s path

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