Bipedal Robot Walking

Optimization-Based Control System

Bipedal robot demonstrating stable walking patterns generated through optimization-based control.

Video demonstration of the bipedal robot's stable walking patterns using optimization-based trajectory generation.

Project Overview

I achieved stable bipedal walking by developing an optimization framework that generates joint trajectories through 6th-order polynomial parameterization. The system optimizes for center of mass (COM) stability and joint constraints via forward kinematics, resulting in smooth and balanced walking motions.

Technical Implementation

The project involved several key technical components:

Trajectory Optimization: Developed an optimization framework that generates optimal joint trajectories using 6th-order polynomial parameterization
COM Stability: Implemented constraints to ensure center of mass stability throughout the walking cycle
Forward Kinematics: Used forward kinematics to validate joint constraints and ensure physically realistic movements
Cyclic Walking: Implemented symmetric left-right swing trajectories with smooth transitions for continuous bipedal locomotion

Key Achievements

Successfully achieved stable bipedal walking through sophisticated trajectory optimization
Implemented cyclic walking by generating symmetric left-right swing trajectories
Created smooth transitions between steps for continuous bipedal locomotion
Developed a mathematically sound approach to bipedal locomotion based on optimization principles

Technologies Used

Programming: Python, MATLAB
Techniques: Trajectory Optimization, Forward Kinematics, Robot Dynamics
Mathematics: 6th-order Polynomial Parameterization, Constrained Optimization
Robotics: Bipedal Locomotion, Joint Control

This project demonstrates my ability to apply advanced optimization techniques and robot dynamics principles to solve complex problems in legged locomotion.

View project code on GitHub