This paper presents NavWareSet, a novel dataset crafted to advance socially compliant robot navigation research. NavWareSet provides multi-modal recordings of both socially compliant and non-compliant robot trajectories in controlled indoor environments. Drawing upon seven carefully selected scenarios, it captures complex human-robot interactions and a range of navigation challenges that mirror realistic social contexts. NavWareSet establishes a rich dataset for evaluating and training navigation algorithms by incorporating two distinct robot platforms—Toyota Human Support Robot (HSR) and Clearpath’s Jackal—and systematically varying their navigation behaviors. With data modalities spanning lidar, RGB-D camera, odometry, and human position annotations, NavWareSet enables fine-grained analysis of the robot’s decision-making process and its impact on human comfort and safety. Ultimately, this dataset provides a versatile resource for developing robust, ethically guided navigation policies and for measuring their performance across a range of social situations. More information can be seen at: https://anr-navware.github.io/navwareset/.
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