Evolution of Socially-Aware Robot Navigation

In recent years, commercial and research interest in service robots working everyday environments has grown. These devices are expected to move autonomously crowded environments, maximizing not only movement efficiency safety parameters, but also social acceptability. Extending traditional path planning modules with socially aware criteria, while maintaining fast algorithms capable of reacting human behavior without causing discomfort, can be a complex challenge. Solving this challenge involved the development proactive systems that take into account cooperation (and interaction) people around them, determined incorporation approaches based on Deep Learning, or fusion skills coming from field human–robot interaction (speech, touch). This review analyzes navigation classifies them according strategies followed by robot manage (or cooperation) humans.