Quadruped Robot Stabilization

This project focuses on stabilizing a quadruped robot using fuzzy control based on yaw angle readings from an IMU sensor. The robot has a mammal-like design with three degrees of freedom per leg, enabling movement through inverse kinematics and gait planning.

System Analysis

• The quadruped robot has three joints per leg: hip, thigh, and knee.
• Leg segments include coxa, femur, and tibia, each controlled by servo motors.
• The robot moves using walk and trot gaits, generated through gait planning and inverse kinematics.
• Yaw stabilization is achieved via fuzzy control, adjusting servo angles to maintain balance.
• Performance criteria include:
  1. The robot returns to the set point after deviation.
  2. Movement remains within predefined limits.
  3. Fuzzy-controlled movement shows lower peak and total error than uncontrolled movement.

Folder Structure

• exportData.py → Exports data for analysis in CSV format.
• fuzzyControl.py → Implements fuzzy logic for leg movement control.
• gait.py → Defines walk and trot gait algorithms.
• globals.py → Declares and initializes global variables.
• legKinematics.py → Computes inverse kinematics for leg movement.
• library.py → Includes necessary libraries.
• main.py → Main program execution.
• sensor.py → Reads data from the IMU sensor.
• servoController.py → Controls servo motors for leg movement.