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5.2 Bipedal locomotion and balance control

Chapter: Bipedal Locomotion and Balance Control

🦾 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.

🧠 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

🧍‍♂️ 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

⚙️ 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

🌀 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      |
              +-----------------------------+

🤖 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)

🧪 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()

🏭 7. Real-World Applications

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

📝 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.

❓ 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

✅ Correct Answers

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