5.2 Bipedal locomotion and balance control

Chapter: Bipedal Locomotion and Balance Control

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🦾 Introduction

Bipedal locomotion ka matlab hai humanoid robot ka do paon par chalna, balance maintain karna, aur different terrains par stable movement karna. Yeh robotics ka sabse challenging area hai because:

• Robot ko continuously center of mass (CoM) balance karna hota hai.
• Har step ke dauran ZMP (Zero Moment Point) maintain karna hota hai.
• Walking cycles, gait patterns, aur real-time control algorithms chal rahe hote hain.

NVIDIA Isaac Sim aur Isaac SDK humanoid locomotion ko train karne ke liye powerful physics simulation environments provide karte hain.

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🧠 1. Fundamentals of Bipedal Locomotion

Bipedal locomotion ke core elements:

• Gait cycle (stance + swing phase)
• Balance control (stability during motion)
• Foot placement (correct angle + position)
• Dynamic walking vs static walking

🌐 Static Walking

• CoM hamesha support polygon ke andar hota hai
• Slow but stable

⚡ Dynamic Walking

• CoM polygon se bahar bhi ja sakta hai
• Fast & natural walking jaisa
• Requires advanced control algorithms

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🧍‍♂️ 2. ZMP – Zero Moment Point

ZMP robotic balance ke liye most important concept hai.

➤ ZMP = point where total moments become zero
Agar ZMP support foot area ke andar rahe → robot stable.
ZMP bahar chale jaaye → robot fall.

Formula (Conceptual):

ZMP = (Sum of torques by inertia + gravity) / Total vertical force

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⚙️ 3. Humanoid Balance Control System

Balance maintain karne ke liye robot use karta hai:

• IMU Sensors (orientation, gyro, acceleration)
• Force/Torque Sensors (foot pressure)
• Joint Encoders (angles)
• Real-time feedback controllers

Controllers Used:

• PID Control
• LQR (Linear Quadratic Regulator)
• MPC (Model Predictive Control) – advanced humanoids

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🌀 4. Bipedal Walking Workflow Diagram

              +-----------------------------+
              |   Humanoid Robot Model      |
              | (Joints, Legs, Sensors)     |
              +--------------+--------------+
                               |
                               v
              +-----------------------------+
              |     Sensor Input Layer       |
              |  - IMU Data                  |
              |  - Foot Pressure             |
              |  - Joint Angle Feedback      |
              +--------------+--------------+
                               |
                               v
              +-----------------------------+
              |  Balance Controller (ZMP)    |
              |  - Maintain CoM              |
              |  - Stability Constraints     |
              +--------------+--------------+
                               |
                               v
              +-----------------------------+
              |   Gait Generator             |
              | - Step length                |
              | - Foot trajectory            |
              | - Swing/Stance timing        |
              +--------------+--------------+
                               |
                               v
              +-----------------------------+
              |   Joint Control System       |
              | - Torques                    |
              | - Motor Positions            |
              +--------------+--------------+
                               |
                               v
              +-----------------------------+
              |  Robot Walking Movement      |
              +-----------------------------+

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🤖 5. Isaac Sim for Bipedal Locomotion

NVIDIA Isaac Sim humanoid simulation provide karta hai with:

• PhysX physics engine
• Real terrain simulation
• Custom humanoid skeletons
• RL-based locomotion (PPO)

Example Use Cases:

• Rough terrain walking
• Stair climbing
• Balance recovery
• Push recovery (robot ko push do → robot khud balance seekhe)

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🧪 6. Example (Pseudo-code: Balance Control)

imu = robot.get_imu_data()
ft = robot.get_foot_force()
com = robot.compute_center_of_mass()

zmp = compute_zmp(ft, com)

if zmp_in_safe_region(zmp):
    robot.walk_forward()
else:
    robot.adjust_posture()

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🏭 7. Real-World Applications

• Humanoid security robots
• Hospital service robots
• Disaster rescue robots
• Elderly assistance humanoids
• Warehouse automation humanoids (Figure-type)

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📝 8. Self Assignment

Tasks:

1. Isaac Sim mein ek humanoid model import karo.
2. IMU + foot sensors ko enable karo.
3. ZMP-based stability check implement karo.
4. Simple gait generator create karo.
5. Test karo robot ka push-recovery behavior.

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❓ 9. MCQs (Multiple Choice Questions)

Q1. ZMP ka main role kya hai?

A. Battery charge karna
B. Stability maintain karna
C. Robot ko paint karna
D. Walking speed badhana

Q2. IMU kya measure karta hai?

A. Internet speed
B. Rotation & acceleration
C. Battery voltage
D. Temperature

Q3. Static walking ka feature kya hai?

A. Bahut fast hota hai
B. CoM support polygon ke andar rehta hai
C. Robot jump karta hai
D. No sensors needed

Q4. Dynamic walking kisko require karta hai?

A. Simple PID only
B. Advanced control + real-time balance
C. No sensors
D. No motor

Q5. Humanoid balance maintain karta hai using:

A. Speaker
B. Camera only
C. IMU + Foot pressure + Joint feedback
D. WiFi

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✅ Correct Answers

1. B
2. B
3. B
4. B
5. C