Chaotic path planners are a subset of path planning algorithms that use chaotic dynamical systems to generate trajectories throughout an environment. These path planners are imperative in surveillance tasks in the presence of adversarial agents which require the paths to be unpredictable while at the same time guaranteeing complete coverage of the environments. In the online coverage of unknown terrain, the chaotic path planning algorithms can work without the need of the environment map and the designer has additional control over the generated paths relative to other heuristic coverage path planners such as random-walk algorithms. Although chaotic path planners have been studied over the past two decades, there has not been an updated survey on the advances. This paper presents an up-to-date review by providing: an introduction of commonly used chaotic systems and methods for their manipulation; an overview of obstacle avoidance methods used by chaotic path planners; and a discussion on other applications, challenges, and research gaps.