The Social Context of Human-Robot Interactions
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Abstract (arXiv)
The Human-Robot Interaction (HRI) community often highlights the social context of an interaction as a key consideration when designing, implementing, and evaluating robot behavior. Unfortunately, researchers use the term "social context" in varied ways. This can lead to miscommunication, making it challenging to draw connections between related work on understanding and modeling the social contexts of human-robot interactions. To address this gap, we survey the HRI literature for existing definitions and uses of the term "social context". Then, we propose a conceptual model for describing the social context of a human-robot interaction. We apply this model to existing work, and we discuss a range of attributes of social contexts that can help researchers plan for interactions, develop behavior models for robots, and gain insights after interactions have taken place. We conclude with a discussion of open research questions in relation to understanding and modeling the social contexts of human-robot interactions.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 21 of its 137 references that are in the map. First posted on arXiv 19 Aug 2025.
Builds on
21 of 137 references.
References · 21
- 2024OpenVLA: An Open-Source Vision-Language-Action Modelcited by 2,887
- 2018Relational inductive biases, deep learning, and graph networkscited by 1,360
- 2023Open X-Embodiment: Robotic Learning Datasets and RT-X Modelscited by 862
- 2020The EMPATHIC Framework for Task Learning from Implicit Human Feedbackcited by 38
- 2022Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfacescited by 19
- 2023Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarioscited by 17
- 2022Causal Discovery of Dynamic Models for Predicting Human Spatial Interactionscited by 14
- 2021AVGCN: Trajectory Prediction using Graph Convolutional Networks Guided by Human Attentioncited by 12
- 2022Social-PatteRNN: Socially-Aware Trajectory Prediction Guided by Motion Patternscited by 12
- 2022It Takes Two: Learning to Plan for Human-Robot Cooperative Carryingcited by 12
- 2020Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Contextcited by 8
- 2020An Approach to Deploy Interactive Robotic Simulators on the Web for HRI Experiments: Results in Social Robot Navigationcited by 7
9 more
- 2019Graph Neural Networks for Human-aware Social Navigationcited by 5
- 2022Virtual, Augmented, and Mixed Reality for Human-Robot Interaction: A Survey and Virtual Design Element Taxonomycited by 5
- 2023Learning Coordination Policies over Heterogeneous Graphs for Human-Robot Teams via Recurrent Neural Schedule Propagationcited by 5
- 2019Robot Learning via Human Adversarial Gamescited by 3
- 2020Learning Whole-Body Human-Robot Haptic Interaction in Social Contextscited by 3
- 2021A Deep Learning Approach To Multi-Context Socially-Aware Navigationcited by 3
- 2023SocNavGym: A Reinforcement Learning Gym for Social Navigationcited by 3
- 2023Robot Navigation in Risky, Crowded Environments: Understanding Human Preferencescited by 2
- 2023Predicting Human Perceptions of Robot Performance During Navigation Taskscited by 2
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Citing papers per year: 2026: 1.
1 paper.