RoboticsProjectsHub

A collection of robotics simulation projects focusing on path planning, obstacle avoidance, kinematics, and computer vision integration. This repository contains a variety of robotics applications and algorithms implemented in Python.

Table of Contents

• Bug Algorithms
• Interactive 2-Link Manipulator
• Math Function Rotator
• Simple Path Planning in a Square Room
• Image Coordinates to Real-World Coordinates
• Requirements
• License

Bug Algorithms

Implementation of classical Bug algorithms (Bug 0, Bug 1, and Bug 2) for robot path planning with obstacle avoidance.

Features:

• Bug 0: Greedy algorithm that moves towards the goal until hitting an obstacle, then moves around it until it can resume direct goal-seeking
• Bug 1: Enhanced algorithm that traverses the entire obstacle perimeter to find the closest point to the goal
• Bug 2: Optimized algorithm that follows the M-line (start-to-goal line) when possible

Usage:

python bug_algorithms/code.py

You can specify which bug algorithm to run by modifying the parameters at the end of the script:

if __name__ == '__main__':
    main(bug_0=True, bug_1=False, bug_2=False)

Interactive 2-Link Manipulator

A 2-link robotic arm simulation that tracks a line function in its workspace.

Features:

• Inverse kinematics to calculate joint angles
• Calculation of workspace reachability
• Animation of the manipulator's movement

Usage:

For the analysis script:

python interactive_2-link_manipulator/Answer.py

For the interactive simulation:

python interactive_2-link_manipulator/Simulation_Animation.py

Math Function Rotator

An interactive visualization tool for rotating mathematical functions.

Features:

• Interactive slider for rotation angle control
• Toggle between different mathematical functions (sin, cos, tan)
• Real-time visualization of both original and rotated functions

Usage:

python math_function_rotator/MathFunctionRotator.py

Simple Path Planning in a Square Room

Implementation of Breadth-First Search (BFS) for path planning in a discretized environment.

Features:

• Grid-based path planning
• Obstacle avoidance
• Animated visualization of path discovery

Usage:

python simple_path_planning_in_a_square_room/Answer.py

Image Coordinates to Real-World Coordinates

A system for transforming camera image coordinates into real-world coordinates for robotic manipulation, integrated with CoppeliaSim.

Features:

• Camera-to-world coordinate transformation
• Interactive click-to-move functionality
• Integration with CoppeliaSim's Remote API
• Control of a redundant robotic manipulator

Requirements:

• CoppeliaSim (formerly V-REP)
• ZMQ Remote API client for CoppeliaSim
• OpenCV

Usage:

1. Start CoppeliaSim and load the redundantRobot-python.ttt scene
2. Run the main script:

python transforming_image_coordinates_to_real_world_coordinates/main.py

3. Click on the camera view to command the robot to move to that location

Requirements

• Python 3.7+
• NumPy
• Matplotlib
• OpenCV (for vision projects)
• Plotly (for interactive visualizations)
• CoppeliaSim (for the robotic manipulation project)
• coppeliasim_zmqremoteapi_client (for CoppeliaSim communication)

Install Python dependencies:

pip install numpy matplotlib opencv-python plotly

License

This project is licensed under the MIT License - see the LICENSE file for details.