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Chapter 2: Basics of Humanoid Robotics

Learning Objectives​

By the end of this chapter, you will be able to:

  • Understand the mechanical structure of humanoid robots
  • Identify key actuator technologies and their trade-offs
  • Explain the role of sensors in humanoid perception and control
  • Describe the fundamentals of robot kinematics and dynamics

Introduction​

Humanoid robots are designed to mimic human form and movement. Their bipedal structure and anthropomorphic design enable them to navigate human environments and use tools designed for people.

Building humanoid robots presents unique engineering challenges: achieving stable bipedal locomotion, coordinating dozens of degrees of freedom, and maintaining balance under dynamic conditions.

Core Concepts​

Mechanical Fundamentals​

Degrees of Freedom (DOF)​

A degree of freedom is an independent direction of motion. Human-like robots typically have:

  • Arms: 7 DOF per arm (shoulder: 3, elbow: 1, wrist: 3)
  • Legs: 6 DOF per leg (hip: 3, knee: 1, ankle: 2)
  • Torso: 3 DOF (pitch, roll, yaw)
  • Head: 2-3 DOF (pan, tilt, optional roll)

Total: 25-30 DOF for a full humanoid

Kinematic Chains​

  • Serial chain: Joints connected in sequence (like an arm)
  • Parallel chain: Multiple actuators control a single joint (increased strength)
  • Closed-loop chain: Forms a loop (used in legs for stability)

Actuator Technologies​

1. Electric Motors​

Advantages:

  • Precise position control
  • High repeatability
  • Easy to integrate with digital controllers

Types:

  • DC brushless motors: High efficiency, long lifespan
  • Servo motors: Built-in position feedback
  • Stepper motors: Precise incremental motion

2. Hydraulic Actuators​

Advantages:

  • High power-to-weight ratio
  • Suitable for heavy-duty applications

Disadvantages:

  • Requires hydraulic pump and fluid management
  • Maintenance-intensive
  • Risk of leaks

3. Pneumatic Actuators​

Advantages:

  • Compliant (safe for human interaction)
  • Lightweight

Disadvantages:

  • Lower precision than electric motors
  • Requires compressed air source

Sensors for Perception and Control​

Vision Sensors​

  • RGB cameras: Color imaging for object recognition
  • Depth cameras (e.g., RealSense): 3D environment mapping
  • Stereo cameras: Depth perception through parallax

Proprioceptive Sensors​

  • Encoders: Measure joint angles (position feedback)
  • IMU (Inertial Measurement Unit): Detects orientation and acceleration
  • Force/Torque sensors: Measure interaction forces at joints

Tactile Sensors​

  • Pressure sensors: Detect contact and grip force
  • Skin sensors: Distributed touch sensing on robot surface

Kinematics and Dynamics​

Forward Kinematics​

Given joint angles, calculate the end-effector position:

Position = f(θ₁, θ₂, ..., θₙ)

Example: With 3 joint angles (shoulder, elbow, wrist), determine where the hand is in 3D space.

Inverse Kinematics​

Given desired end-effector position, calculate required joint angles:

(θ₁, θ₂, ..., θₙ) = f⁻¹(desired position)

Challenge: Often has multiple solutions or no solution (workspace limits).

Dynamics​

Dynamics govern how forces and torques affect motion. The equation of motion:

τ = M(q)q̈ + C(q,q̇)q̇ + G(q)

Where:

  • τ: Joint torques (control input)
  • M(q): Inertia matrix
  • C(q,q̇): Coriolis and centrifugal forces
  • G(q): Gravity forces

Practical Application​

Walking Control​

Humanoid walking requires:

  1. Gait planning: Define foot trajectories and center of mass motion
  2. Balance control: Keep center of pressure within support polygon
  3. Compliance: Absorb impacts and adapt to uneven terrain

Zero Moment Point (ZMP) is a key stability criterion: the point where the net moment from gravity and inertia is zero.

Example: Simple Balance Controller​

# Pseudocode for balance control
def balance_controller(imu_data, target_orientation):
    error = target_orientation - imu_data.orientation
    torque_correction = PID_control(error)
    apply_torque_to_ankle_joints(torque_correction)

This simple controller adjusts ankle torques to maintain upright posture.

Summary​

Humanoid robots combine mechanical design, actuation, sensing, and control to achieve human-like motion. The field draws on mechanical engineering, control theory, and AI to create machines that can navigate and interact with human environments.

Key Takeaways:

  • Humanoids have 25-30 degrees of freedom to mimic human motion
  • Actuator choice (electric, hydraulic, pneumatic) involves trade-offs in power, precision, and safety
  • Sensors provide feedback for perception (vision) and control (encoders, IMUs)
  • Kinematics and dynamics are essential for planning and executing motion

Further Reading​

  • Books:

    • Humanoid Robotics: A Reference by Ambarish Goswami and Prahlad Vadakkepat
    • Introduction to Robotics: Mechanics and Control by John J. Craig

  • Research Papers:

    • "Bipedal Walking Control Based on Capture Point Dynamics" (IROS 2011)
    • "Atlas: A Hydraulic Humanoid Robot" by Boston Dynamics

  • Online Resources: