README.md

metadata

title: Interactive Arm Simulator
emoji: 🚀
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.36.2
app_file: app.py
tags:
  - robotics
  - inverse-kinematics
  - gradio
  - python
  - simulation
  - education
  - visualization
  - arm-simulator
  - interactive
  - STEM
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/653637973da0ff3c70cac1b5/grSqNUonDS7CApHsbnc8U.png
license: mit
pinned: true
short_description: Interactive 2-DOF robotic arm simulator with real-time inver

Interactive Arm Simulator

A modern, interactive Gradio app for simulating the inverse kinematics of a 2-DOF (two-degree-of-freedom) robotic arm. Visualize, experiment, and learn the math behind robotic arm movement in real-time!

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🚀 Features

• Live Simulation: Adjust target coordinates (X, Y) and arm lengths (L1, L2) with sliders and see the arm move instantly.
• Visual Feedback: Clear visualization of the arm, joints, and unreachable targets.
• Angle Display: See calculated joint angles (shoulder and elbow) in both radians and degrees.
• Math Explanation: Built-in accordion explains the inverse kinematics formulas.
• Copyable Python Code: Easily grab the core function to use in your own projects.

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🕹️ Controls Preview

Use the sliders to set the arm lengths and target position. The plot updates in real-time.

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📦 Usage

1. Install requirements:

   pip install gradio matplotlib numpy
   

2. Run the app:

   python app.py
   

3. Interact:
   • Move the sliders for X, Y, L1, and L2.
   • Watch the arm and joint angles update.
   • Use the "Copy the Core Python Function" dropdown for your own code.

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🧮 How It Works: Inverse Kinematics

This app calculates the joint angles needed for a 2-link arm to reach a target point (x, y) using geometry:

1. Elbow Angle ($q_2$): Uses the Law of Cosines: $$\cos (q_2)=\frac{x^2+y^2-L_1^2-L_2^2}{2L_1{L}_2}\backslash cos(q\_2)\; =\; \backslash frac\{x^2\; +\; y^2\; -\; L\_1^2\; -\; L\_2^2\}\{2L\_1L\_2\}$$ 2. Shoulder Angle ($q_1$): Combines the angle to the target and the triangle's internal angle: $$q_1=\alpha -\beta q\_1\; =\; \backslash alpha\; -\; \backslash beta$$ Where: - $\alpha = \text{atan2}(y, x)$ (angle to target) - $\beta = \text{atan2}(L_2 \sin(q_2), L_1 + L_2 \cos(q_2))$ If the target is unreachable, the app shows a warning and marks it in red.

📝 Copy the Core Python Function

The app includes a dropdown with the following code for your use: python def inver_k(l1, l2, x, y): """ Calculates the joint angles (q1, q2) for a 2-DOF robotic arm. Args: l1, l2: Lengths of the arm segments x, y: Target coordinates Returns: (success, q1, q2): Whether the point is reachable and the joint angles in radians """ import math import numpy as np dist_sq = x**2 + y**2 if dist_sq > (l1 + l2)**2 or dist_sq < (l1 - l2)**2: return (False, 0, 0) cos_q2 = (dist_sq - l1**2 - l2**2) / (2 * l1 * l2) cos_q2 = np.clip(cos_q2, -1.0, 1.0) q2 = math.acos(cos_q2) alpha = math.atan2(y, x) beta = math.atan2(l2 * math.sin(q2), l1 + l2 * math.cos(q2)) q1 = alpha - beta return (True, q1, q2)

📚 Credits

• Original inverse kinematics logic from ARMv6 by gokul6350
• Adapted and extended as an interactive Gradio app for educational purposes.

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License

MIT