To expand interdisciplinary consideration of the mechanisms involved in navigation, this chapter provides an overview of research into robot navigation. Discussion is intended for a multidisciplinary audience, including non-roboticists, and focuses on modular, probabilistic, and learning-based systems. Ultra-simplistic robot navigation systems such as those found in micro- and nano-robot systems are discussed, and recent developments driven by advances in machine learning, including large language models and vision language models, are outlined. Key components of robot navigation as well as challenges in the field are presented, and points of intersection between artificial and biological systems highlighted. To overcome current challenges, artificial systems must be able to emulate the adaptability, introspective awareness, and efficiency of biological systems. Solving these challenges in robots may, in turn, generate new insights into the biological systems from which inspiration has been drawn.