Looking for robotics books in PDF? We've gathered 9 free robotics books covering kinematics, robot programming, autonomous mobile robots, and artificial intelligence.
These books bring together the ideas behind modern robotics: manipulator design, control systems, sensors, and probabilistic algorithms. You will find work from Sebastian Thrun, Roland Siegwart, and other researchers who shaped the field.
Whether you are starting out or already comfortable with industrial automation, there is a book here for you. Every title is free to read online or download as PDF.
Fundamentals
Robotics Fundamentals and Introductions
Start here if you are learning the basics of robotics. These books cover mechanical aspects, kinematics, robot design, and the vocabulary the rest of the field uses.
A university textbook covering the mechanical fundamentals of robotics, including kinematic chains, degrees of freedom, manipulator structures, joint classifications, and robot dynamics. Ideal for engineering students building a solid base in robot mechanics.
An open textbook for students learning autonomous robotics, covering locomotion, kinematics, forward and inverse kinematic problems, perception, sensors, localization, error propagation, and simultaneous localization and mapping. Released as an Open Educational Resource through LibreTexts.
A mechatronics thesis that walks through the core concepts of robot design, including degrees of freedom, trajectory planning, servo motor selection, hydraulics, pneumatics, and programmable logic. Written to give beginners a practical orientation in how robots are built.
Once you know how a robot moves, the next step is making it decide. These books cover computer vision with OpenCV, probabilistic algorithms from Sebastian Thrun, and the intersection between AI and robotics.
A textbook on intelligent robotics using OpenCV, covering robot vision, mobile robots, manipulators, microcontroller-based control, and image processing implementations. Ideal for hands-on learners moving from theory to code.
A UK-RAS white paper from researchers at Imperial College London reviewing the intersection of artificial intelligence and robotics, covering machine learning, healthcare robots, autonomous systems, and the societal impact of intelligent automation.
Sebastian Thrun's Carnegie Mellon survey paper introducing probabilistic robotics: Bayes filters, particle filters, Markov localization, and POMDPs. A compact overview of the ideas that now underpin most modern autonomous systems.
An introduction to mobile robotics spanning locomotion, wheel kinematics, sensors for navigation, perception, feature extraction, localization algorithms, and motion planning. A foundational reference for engineers working with wheeled and legged robots.
A PhD thesis covering soft robotic systems: design principles, flexible materials, actuation technologies, control strategies, and real-world applications in medical and industrial contexts. A rigorous academic treatment of a fast-growing field.
A UNIDIR report on swarm robotics examining the technical and operational principles behind coordinated autonomous systems. Draws on expert interviews to map the capabilities, limitations, and policy implications of multi-robot swarms.