Enabling Robots to Adhere to Social Norms by Detecting F-Formations
Abstract: Robot navigation in environments shared with humans should take into account social structures and interactions. The identification of social groups has been a challenge for robotics as it encompasses a number of disciplines. We propose a hierarchical clustering method for grouping individuals into free standing conversational groups (FSCS), utilising their position and orientation. The proposed method is evaluated on the SALSA dataset with achieved F1 score of 0.94. The algorithm is also evaluated for scalability and implemented on a mobile robot attempting to detect social groups and engage in interaction.
Recommended citation: Kollakidou, A., Naik, L., Palinko, O., & Bodenhagen, L. (2021, August). Enabling Robots to Adhere to Social Norms by Detecting F-Formations. In 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) (pp. 110-116). IEEE.