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Humanoid Robots with AI and Simulation

The Complete Guide to Designing Humanoid Robotics and AI Systems

gareth thomas

If you want to understand humanoid robotics at its core—this book is your roadmap.

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Humanoid Robotics: From Design to Deployment

Robotics is no longer child’s play. The real breakthroughs don’t come from flashy demos or science fiction fantasies. They come from the hard, mathematical truths that govern how machines move, think, and interact with the world.

That’s exactly what this book delivers. Not hype. Not watered-down explanations. But the rigorous foundations of humanoid robotics—laid out with the equations, models, and theory you need to understand the field at a serious level.

Inside, you’ll discover:

  • The mechanical and electrical principles that define balance, power, and coordination in humanoids.
  • The mathematics of motion—kinematics, dynamics, and control systems that explain why a robot can or cannot walk.
  • The frameworks of intelligence—ROS/ROS2, simulation, reinforcement learning, and behavior architectures, grounded in theory.
  • The science of perception—computer vision, SLAM, and sensor fusion analyzed through formulas and rigorous models.
  • The wider implications—ethics, safety, and the theoretical challenges of deploying humanoids in real society.

This is not a casual overview. It is a serious academic text, built for readers who demand depth, precision, and intellectual challenge. If you want the entertainment value of sci-fi, look elsewhere. If you want to understand humanoid robotics at its core—this book is your roadmap.

The theory is here. The formulas are here. The future belongs to those who master them.

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Author

About the Author

gareth thomas

Gareth Thomas is the publisher-author behind BurstBooks, creating rigorous, code-rich STEM textbooks for engineers and advanced learners. Based in Auckland, New Zealand, he builds practical, reference-grade titles that blend clear exposition with working math, diagrams, and real-world examples. His catalog focuses on high-impact domains—including humanoid robotics, GPU architecture and programming, electronic warfare systems, satellite and space systems, EEG/neuro-engineering, and applied AI/ML—designed for hands-on use in labs, teams, and self-study.

Gareth’s workflow is unapologetically modern: LaTeX for precision, reproducible figures and listings, and AI-assisted drafting to accelerate iteration while maintaining strict technical accuracy. Each BurstBooks edition aims to minimize fluff and maximize utility—clean structure, consistent notation, and actionable takeaways. When possible, he complements books with supporting Github repositories, infographics, and exercises to help readers move from theory to implementation quickly.

Note: Many BurstBooks titles are AI-assisted technical editions—structured for information density and correctness over prose style.

Contents

Table of Contents

Humanoid Robotics — Outline

Chapter 1. Introduction to Robotics and NVIDIA Tools

Section 1. The Evolution of Robotics

  • History of robotics
  • Modern trends in robotics
  • Rise of humanoid robots
  • Ethical and societal implications

Section 2. NVIDIA Robotics Ecosystem

  • Overview of Isaac Sim
  • Introduction to GROOT for Behavior Trees
  • Role of Omniverse in robotics
  • Key features of NVIDIA SDK

Section 3. Preparing Your Development Environment

  • System requirements
  • Installing Isaac Sim and SDK
  • Setting up GROOT and Omniverse
  • First steps: Running a simulation example

Chapter 2. Anatomy of Humanoid Robots

Section 1. Mechanical Anatomy

  • Skeletal structure of humanoid robots
  • Actuators and their applications
  • Degrees of freedom in humanoid robots
  • Challenges in humanoid balance

Section 2. Electrical Components

  • Sensors and their placement
  • Power systems: Batteries vs wired
  • Microcontrollers and processors
  • Communication systems

Section 3. Integration of Mechanical and Electrical Systems

  • Synchronization challenges
  • Designing for efficiency
  • Maintenance considerations
  • Troubleshooting common issues

Chapter 3. Fundamentals of Mechanical Design

Section 1. Tools for Mechanical Design

  • CAD software overview
  • Using Omniverse for mechanical simulation
  • Practical design tips for humanoids
  • Case study: Building a robotic hand

Section 2. Materials and Fabrication

  • Structural materials for robotics
  • 3D printing and CNC machining
  • Balancing strength and flexibility
  • Environmental considerations

Section 3. Assembly and Testing

  • Assembling mechanical components
  • Stress testing the framework
  • Troubleshooting mechanical faults
  • Real-world challenges in assembly

Chapter 4. Electrical Engineering for Robotics

Section 1. Power Systems

  • Choosing a power source
  • Managing battery life
  • Safety in electrical design
  • Testing and monitoring power systems

Section 2. Sensor Integration

  • Types of sensors (vision, IMUs, etc.)
  • Sensor calibration techniques
  • Data acquisition and processing
  • Real-world case study: Obstacle detection

Section 3. Control Systems

  • Basics of motor control
  • Closed-loop vs open-loop systems
  • Real-time data processing
  • Challenges in humanoid motion control

Chapter 5. Software Fundamentals

Section 1. Introduction to Robotics Operating Systems

  • Overview of ROS and ROS2
  • Setting up ROS for humanoid robots
  • Basic ROS nodes and topics
  • Debugging with ROS tools

Section 2. Behavior Tree Basics

  • Fundamentals of decision-making in robotics
  • Creating Behavior Trees in GROOT
  • Debugging and optimizing trees
  • Advanced patterns in tree design

Section 3. Integrating Software and Hardware

  • Real-time control with ROS
  • Communicating with sensors and actuators
  • Synchronization challenges
  • Best practices in system integration

Chapter 6. Training Humanoids in Simulation

Section 1. Isaac Sim Fundamentals

  • Setting up simulation environments
  • Building virtual twins
  • Physics-based simulation features
  • Debugging simulation issues

Section 2. Data Collection and Training

  • Generating synthetic training data
  • Training perception models
  • Reinforcement learning basics
  • Evaluating model performance

Section 3. Transitioning to Real Robots

  • Transferring trained models
  • Bridging the simulation-reality gap
  • Testing in real-world conditions
  • Continuous training cycles

Chapter 7. Perception and Vision Systems

Section 1. Fundamentals of Computer Vision

  • Object detection and classification
  • Depth perception and stereo vision
  • Key challenges in visual processing

Section 2. Integrating Vision with Robotics

  • Vision sensors and hardware
  • Building vision pipelines
  • Case study: Gesture recognition

Section 3. Advanced Vision Techniques

  • Semantic segmentation
  • Visual SLAM for humanoids
  • Using pretrained models
  • Future trends in robotic vision

Chapter 8. Motion Planning and Control

Section 1. Basics of Motion Control

  • Understanding kinematics and dynamics
  • Balancing algorithms
  • Case study: Humanoid walking

Section 2. Advanced Motion Planning

  • Pathfinding algorithms
  • Reactive vs proactive planning
  • Collision avoidance techniques

Section 3. Optimization and Challenges

  • Improving efficiency in motion
  • Handling unexpected obstacles
  • Scaling motion planning to complex tasks
  • Common pitfalls in humanoid control

Chapter 9. Advanced Behavior Design

Section 1. Extending Behavior Trees

  • Complex tree structures
  • Hybrid approaches to decision-making
  • Case study: Multi-task robots

Section 2. Collaboration and Teamwork

  • Multi-robot coordination
  • Implementing swarm intelligence
  • Case study: Collaborative humanoids

Section 3. Ethical Behavior in Robotics

  • Decision-making constraints
  • Avoiding unintended behaviors
  • Regulatory and ethical considerations

Chapter 10. Human-Robot Interaction

Section 1. Fundamentals of HRI

  • Understanding human factors
  • Designing intuitive interactions
  • Case study: Voice-command robots

Section 2. Advanced Interaction Methods

  • Natural language processing in robotics
  • Emotion recognition
  • Gesture-based controls

Section 3. Applications of HRI

  • Robots in healthcare
  • Educational humanoid systems
  • Assistive robotics for disabilities

Chapter 11. Autonomous Navigation

Section 1. Basics of SLAM

  • Understanding Simultaneous Localization and Mapping
  • Mapping techniques for humanoids
  • Sensor fusion for improved accuracy
  • Case study: Indoor navigation

Section 2. Path Planning Algorithms

  • Graph-based methods (A*, Dijkstra's)
  • Sampling-based methods (RRT, PRM)
  • Hybrid approaches to pathfinding
  • Real-world examples: Avoiding obstacles

Section 3. Challenges in Navigation

  • Handling dynamic environments
  • Navigating uneven terrain
  • Dealing with sensor noise
  • Improving robustness and efficiency

Chapter 12. Reinforcement Learning for Robotics

Section 1. Fundamentals of Reinforcement Learning

  • Key concepts: States, actions, rewards
  • Exploration vs exploitation trade-offs
  • Designing reward functions for robots
  • Case study: Balancing a humanoid

Section 2. Training Robots in Simulation

  • Using Isaac Sim for RL environments
  • Transferring learned behaviors to hardware
  • Avoiding overfitting to simulation

Section 3. Applications of RL

  • Humanoid walking and running
  • Object manipulation tasks
  • Cooperative robotics using RL
  • Future trends in RL for robotics

Chapter 13. Collaborative Robotics

Section 1. Introduction to Multi-Robot Systems

  • Benefits of collaboration
  • Designing communication protocols
  • Task allocation strategies

Section 2. Swarm Intelligence

  • Fundamentals of swarm robotics
  • Implementing decentralized control
  • Case study: Multi-humanoid assembly task

Section 3. Real-World Applications

  • Collaborative robots in manufacturing
  • Disaster response robotics
  • Future of collaborative humanoid robots

Chapter 14. Real-World Robotics Applications

Section 1. Robots in Healthcare

  • Assistive robots for elderly care
  • Robots in surgery and rehabilitation
  • Challenges in medical robotics

Section 2. Robots in Education

  • Teaching STEM with humanoid robots
  • Interactive learning experiences
  • Case study: Robots in classrooms

Section 3. Robots in Industry

  • Humanoids in logistics and warehousing
  • Advanced manufacturing tasks
  • Ethical and practical challenges

Chapter 15. Debugging and Troubleshooting

Section 1. Mechanical Troubleshooting

  • Identifying common mechanical failures
  • Best practices for maintenance
  • Case study: Fixing actuator malfunctions

Section 2. Software Debugging

  • Debugging with ROS and GROOT
  • Common software pitfalls in robotics
  • Tools for performance analysis

Section 3. Debugging Integration Issues

  • Diagnosing communication errors
  • Handling synchronization problems
  • Testing in real-world environments

Chapter 16. Ethics and Safety in Robotics

Section 1. Ethical Implications of Humanoid Robots

  • Privacy concerns with robots
  • Impacts on employment and society
  • Designing for inclusivity and fairness

Section 2. Ensuring Safety in Robotics

  • Safety protocols for humanoids
  • Handling failures gracefully
  • Best practices for safe operation

Section 3. Regulatory Compliance

  • Navigating global robotics regulations
  • Certification processes for robots
  • Case study: Meeting safety standards

Chapter 17. Future Trends in Robotics

Section 1. Advances in AI for Robotics

  • Emerging AI models for control
  • Integrating generative AI with robotics
  • Case study: Predictive maintenance

Section 2. Robotics in Space and Exploration

  • Humanoids in space missions
  • Challenges of robotic exploration
  • Future possibilities for space humanoids

Section 3. Emerging Applications

  • Robots in entertainment and gaming
  • Autonomous robots in agriculture
  • Pushing the boundaries of humanoid design

Chapter 18. Case Study: Building a Complete Humanoid Robot

Section 1. Starting from Scratch

  • Defining requirements and goals
  • Planning the design and build process
  • Managing costs and timelines

Section 2. Step-by-Step Implementation

  • Designing the mechanical structure
  • Programming the control software
  • Training the robot in simulation
  • Testing and deploying the robot

Section 3. Lessons Learned and Future Directions

  • Challenges faced during development
  • Optimizing for scalability
  • Next steps in humanoid robotics

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