Robotics, Foundations and Frameworks Series

Robotics comes down to one loop: sense the world, work out what the readings mean, choose an action, and carry it out. This book shows you how engineers build each part of that loop, including the math of a moving arm and the AI models that now steer humanoid robots.

The chapters follow the order in which problems appear when you actually try to build a robot.

Each one starts with machines you already know, such as the Perseverance rover, Amazon warehouse robots, da Vinci surgical systems, and the vacuum cleaning your living room, then explains the methods that make them work.

Later chapters build directly on earlier ones, so the ideas stack up in a logical order.

Ten chapters walk through:

- What counts as a robot, plus degrees of freedom, workspace, payload, and the difference between accuracy and repeatability

- Coordinate frames, quaternions, Denavit-Hartenberg parameters, forward and inverse kinematics, and the Jacobian

- Motors, harmonic drives, hydraulics, and batteries

- Encoders, IMUs, lidar, stereo cameras, and deep learning methods that turn raw sensor data into recognized objects and 6D poses

- PID tuning, integrator windup, state-space models, LQR, model predictive control, and the impedance control that lets an arm touch things gently

- Kalman filters, particle filters, SLAM, and path planning with A* and RRT

- Walking, flying, swimming, and grasping

- ROS 2, behavior trees, Gazebo and MuJoCo simulation, reinforcement learning, imitation learning, and the vision-language-action models that Google DeepMind and Physical Intelligence have trained since 2023

- Cobots that work beside people without safety cages, teleoperation, shared autonomy, and swarms

- ISO 10218 safety rules, labor displacement, liability, privacy, autonomous weapons, and the research problems nobody has solved yet

High school algebra and some trigonometry are enough to follow the math, and worked numbers show up throughout. Every chapter ends with questions that ask you to apply ideas to new situations, and example responses at the back let you check your reasoning. A historical timeline, a glossary, works cited, and recommended readings round out the reference material.

This book fits readers such as:

- Students deciding on an engineering or computer science major

- Workers whose jobs now involve automation

- Hobbyists wiring up a first Arduino build

- Anyone who wants to argue about robots and employment using facts

Read the chapters in order if you are new to the field, or jump straight to the topics you need and lean on the glossary. Either way, you will come away able to read a research paper or a job posting without stalling on vocabulary.

You will also know the four questions to ask when a slick humanoid demo hits the news: was a person driving it, was the video sped up, how many attempts did it take, and was the set staged?