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Path planning is an essential component of mobile robotics. Classical path planning algorithms, such as wavefront and rapidly exploring random tree, are used heavily in autonomous robots. With the recent advances in machine learning, development of learning-based path planning algorithms has been experiencing a rapid growth. A unified path planning interface that facilitates the development and benchmarking of existing and new algorithms is needed. This paper presents PathBench, a platform for developing, visualizing, training, testing, and benchmarking of existing and future, classical and learning-based path planning algorithms in 2D and 3D grid world environments. Many existing path planning algorithms are supported, e.g. A*, Dijkstra, waypoint planning networks, value iteration networks, and gated path planning networks; integrating new algorithms is easy and clearly specified. The benchmarking ability of PathBench is explored in this paper by comparing algorithms across five different hardware systems and three different map types, including built-in PathBench maps, video game maps, and maps from real world databases. Metrics, such as path length, success rate, and computational time, were used to evaluate algorithms. Algorithmic analysis was also performed on a real-world robot to demonstrate PathBench's support for Robot Operating System. PathBench is open source1. [ABSTRACT FROM AUTHOR]

The novel coronavirus (COVID-19) pandemic has completely changed our lives and how we interact with the world. The pandemic has brought about a pressing need to have effective disinfection practices that can be incorporated into daily life. They are needed to limit the spread of infections through surfaces and air, particularly in public settings. Most of the current methods utilize chemical disinfectants, which can be laborious and time-consuming. Ultraviolet (UV) irradiation is a proven and powerful means of disinfection. There has been a rising interest in the implementation of UV disinfection robots by various public institutions, such as hospitals, long-term care homes, airports, and shopping malls. The use of UV-based disinfection robots could make the disinfection process faster and more efficient. The objective of this review is to equip readers with the necessary background on UV disinfection and provide relevant discussion on various aspects of UV robots. • The COVID-19 pandemic has prompted renewal in disinfection strategies. • A comprehensive introduction on UV disinfection and UV robots is presented. • UV disinfection has shown to offer consistent and efficient disinfection. • UV robots introduce autonomy that could improve existing disinfection procedures. • Research on open problems of autonomous UV disinfection are undergoing and growing. [ABSTRACT FROM AUTHOR]