Theory & Background

Static gait maintains center of gravity within support polygon at all times — robot never topples. 3-legged support always stable. Disadvantage: slow and requires large support base. Dynamic gait (like human walking) allows CoG outside support polygon temporarily — relying on momentum and continuous foot placement to prevent falling. Begin with static gait for validation, then implement dynamic walking for speed.

Components & Requirements

10 components required for this project.

#	Component	Purpose	Qty
1	MG996R Servos	10 DOF joints (5 per leg)	x10
2	PCA9685 PWM Driver	12-channel servo control	x1
3	Arduino Mega	Gait control	x1
4	MPU6050 IMU	Balance monitoring	x1
5	FSR (Force Sensitive Resistors)	Foot pressure detection	x4
6	LiPo 7.4V 4000mAh	Servo power	x1
7	3D-Printed Body Parts	Structure	x1
8	M3 Bolts and Nuts Kit	Assembly hardware	x1
9	Ball Bearings (8mm ID)	Low-friction joint bearings	x12
10	Nylon Horn Adapters	Servo-to-link connections	x10

Step-by-Step Implementation

Follow these 3 steps carefully.

1

Static vs Dynamic Gait Planning

Static gait maintains center of gravity within support polygon at all times — robot never topples. 3-legged support always stable. Disadvantage: slow and requires large support base. Dynamic gait (like human walking) allows CoG outside support polygon temporarily — relying on momentum and continuous foot placement to prevent falling. Begin with static gait for validation, then implement dynamic walking for speed.

2

10-DOF Leg Kinematics

Each leg: hip roll (side lean), hip pitch (fore-aft swing), knee pitch, ankle pitch, ankle roll — 5 DOF × 2 legs = 10 DOF total. Derive inverse kinematics geometrically for 2-link leg (hip to knee = L1, knee to ankle = L2). Given foot position (x,z), compute: θ_knee = acos((x²+z²−L1²−L2²)/(2L1L2)), θ_hip = atan2(x,z) − atan2(L2sin(θ_knee), L1+L2cos(θ_knee)). Ankle compensates for ground level.

3

Gait Pattern Implementation

Define gait cycle phases: Double support (both feet on ground, weight transfer), Single support right (left foot off ground swinging), Double support, Single support left. For each phase, compute feet target positions. Apply IK to get joint angles. Interpolate between keyframes using sinusoidal trajectories for smooth motion. Phase timing: 800ms total cycle (400ms per step) for stable walking at approx 0.2 m/s.

Code & Implementation

Core code for biped_gait.ino:

biped_gait.ino
  C/C++

#include <Wire.h>
#include <Adafruit_PWMServoDriver.h>
Adafruit_PWMServoDriver pwm = Adafruit_PWMServoDriver();
#define SERVOMIN 150 #define SERVOMAX 600

void setAngle(int channel, int deg) {
  int pulse = map(deg, 0, 180, SERVOMIN, SERVOMAX);
  pwm.setPWM(channel, 0, pulse);
}

// Gait keyframes [hip_pitch, knee, ankle_pitch, hip_roll, ankle_roll]
int stand_pose[10] = {90,90,90,90,90, 90,90,90,90,90};
int step_left[10]  = {100,85,95,80,90, 80,90,90,100,85}; // Weight right, swing left

void applyPose(int* pose, int duration) {
  for(int i=0;i<10;i++) setAngle(i, pose[i]);
  delay(duration);
}

void loop() {
  applyPose(stand_pose, 500);
  applyPose(step_left, 800);
  // ... more gait phases
}

Testing & Troubleshooting

Test Bipedal Walking Robot by verifying each subsystem individually before full integration.

!

Troubleshooting Tips

Verify power voltages, check ground connections, use serial monitor for debug.

Real-World Applications

*Humanoid robotics research platform

*Education about legged locomotion

*Motion capture for animation

*Prosthetic leg motion research

*Terrain adaptability research

*Human movement pattern mimicking

*Entertainment and performance robotics

*Rehabilitation exercise demonstration

Extensions & Next Steps

Implement reinforcement learning for adaptive gait optimization
Add terrain perception for stair climbing
Build a compliant ankle joint for better ground adaptation
Implement push recovery with whole-body control
Add vision-based navigation for autonomous indoor mobility

Interactive Playground

Coming Soon

An interactive simulator will be available here — simulate circuits and run code in-browser without hardware.

Frequently Asked Questions

Why does my biped fall to one side when trying to walk?

One-sided falling indicates: unequal servo calibration (zero positions differ between left and right), asymmetric weight distribution (battery or electronics mounted off-center), inadequate hip roll DOF (insufficient lateral weight shifting before lifting a foot), or ankle roll not compensating for terrain angle. Solution: add hip roll servos if not present, calibrate all servos to true 90° in reference pose, measure and log left/right FSR readings during walking to verify weight transfer is occurring correctly.

Introduction