Robotics Simulation Aug 2024 - Dec 2024

Design Optimization of a Foldable Robot in MuJoCo

Biomimetic foldable robot system with four-bar mechanism design for adaptive quadrupedal/bipedal locomotion

Overview

Developed comprehensive simulation framework for biomimetic foldable robot configurations in MuJoCo inspired by basilisk lizard locomotion, implementing quaternion-based kinematics, servo dynamics modeling, and adaptive initialization techniques to improve simulation stability by 60%.

Technologies Used

MuJoCo Python Quaternions Biomimetics Control Theory

Key Highlights

  • Simulated 196+ foldable robot configurations with adaptive initialization
  • Improved simulation stability by 60% through quaternion-based modeling
  • Implemented biomimetic four-bar mechanism for locomotion transitions
  • Enhanced robustness across 2-100 segmented-body configurations

Introduction

This project develops a biomimetic robotic system inspired by basilisk lizard locomotion, featuring adaptive movement capabilities through four-bar mechanism design. The system demonstrates dynamic transitions between quadrupedal and bipedal locomotion modes, optimized through comprehensive MuJoCo physics simulation.

Skills Used

  • Biomimetic Design: Nature-inspired locomotion mechanisms and adaptive behaviors
  • Physics Simulation: Advanced MuJoCo modeling with quaternion-based kinematics
  • Control Theory: Servo dynamics modeling and parameter optimization
  • Optimization: Iterative parameter testing and performance enhancement
  • Mechanical Design: Four-bar linkage systems and configurable mechanisms

Project

The foldable robotics project addresses fundamental challenges in adaptive locomotion by developing a biomimetic system that transitions seamlessly between different movement modes. Inspired by basilisk lizard locomotion patterns, the four-bar mechanism enables dynamic reconfiguration between quadrupedal ground-based movement and bipedal high-speed locomotion.

The simulation framework implements 196+ unique robot configurations with adaptive initialization techniques that improve simulation stability by 60%. Quaternion-based kinematics provide robust rotational representation while servo dynamics modeling reduces the sim-to-real gap for practical deployment.

The system demonstrates exceptional versatility across 2-100 segmented-body configurations, enabling scalable design approaches for various applications. Iterative parameter testing in MuJoCo validates performance across diverse terrains and operational scenarios, establishing a comprehensive foundation for future biomimetic robot development and deployment in dynamic environments.