This book is intended to be an accessible introduction to key algorithmic concepts in autonomousrobotics targeted toward undergraduate computer science students. It is not intended to be an exhaustive reference or to provide rigorous mathematical foundations, derivations or proofs. The focus is on clear explanations with extensive examples and visualizations.This book uses a Python-based pseudocode that is generally very close to executable Python. The author has attempted to steer clear of any idiomatic Python constructs so that the algorithm listings should be easy to follow even for those without a background in the Python language.This book is a work in progress! It covers several of the central algorithmic ideas in autonomousrobotics, but there are still significant missing pieces. In particular, there is currently no coverage ofparticle filters, mapping algorithms, or simultaneous localization and mapping (SLAM). The author welcomes contributions.Table of Contents:Chapter 1: Controlling Physical SystemsChapter 2: Coordinate FramesChapter 3: Path PlanningChapter 4: Probabilistic LocalizationBibliographyIndex