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This article discusses the concept of enhanced human modeling in robotics for socially-aware place navigation. It highlights the challenges faced by robots when navigating in unfamiliar environments and the importance of understanding human activities, intentions, and social dynamics in order to navigate spaces shared with humans. The article also explores various dimensions of human modeling, such as human pose estimation, action recognition, language understanding, and affective computing, and how they contribute to socially aware navigation. It concludes by emphasizing the need for robust and lightweight solutions that enhance human understanding and modeling in robot navigation. [Extracted from the article]