Perceived Safety in Physical Human Robot Interaction -- A Survey
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Abstract (arXiv)
This review paper focuses on different aspects of perceived safety for a number of autonomous physical systems. This is a major aspect of robotics research, as more and more applications allow human and autonomous systems to share their space, with crucial implications both on safety and on its perception. The alternative terms used to express related concepts (e.g., psychological safety, trust, comfort, stress, fear, and anxiety) are listed and explained. Then, the available methods to assess perceived safety (i.e., questionnaires, physiological measurements, behavioral assessment, and direct input devices) are described. Six categories of autonomous systems are considered (industrial manipulators, mobile robots, mobile manipulators, humanoid robots, drones, and autonomous vehicles), providing an overview of the main themes related to perceived safety in the specific domain, a description of selected works, and an analysis of how motion and characteristics of the system influence the perception of safety. The survey also discusses experimental duration and location of the reviewed papers as well as identified trends over time.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 May 2021.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 5.
8 papers.
- 2025Advancing Embodied Agent Security: From Safety Benchmarks to Input Moderationcited by 12
- 2025Minds on the Move: Decoding Trajectory Prediction in Autonomous Driving with Cognitive Insightscited by 10
- 2024MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrationscited by 3
- 2025Affective and Conversational Predictors of Re-Engagement in Human-Robot Interactions -- A Student-Centered Study with A Humanoid Social Robotcited by 3
- 2023Predicting Human Perceptions of Robot Performance During Navigation Taskscited by 2
- 2025ANNIE: Be Careful of Your Robotscited by 2
- 2022FCN-Pose: A Pruned and Quantized CNN for Robot Pose Estimation for Constrained Devicescited by 0
- 2025Tactile Gesture Recognition with Built-in Joint Sensors for Industrial Robotscited by 0
- 2025ANNIE: Be Careful of Your Robots3 Sep 2025
- 2025Tactile Gesture Recognition with Built-in Joint Sensors for Industrial Robots17 Aug 2025
- 2025Advancing Embodied Agent Security: From Safety Benchmarks to Input Moderation22 Apr 2025
- 2025Minds on the Move: Decoding Trajectory Prediction in Autonomous Driving with Cognitive Insights27 Feb 2025
- 2025Affective and Conversational Predictors of Re-Engagement in Human-Robot Interactions -- A Student-Centered Study with A Humanoid Social Robot18 Feb 2025
- 2024MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations10 Jul 2024
- 2023Predicting Human Perceptions of Robot Performance During Navigation Tasks17 Oct 2023
- 2022FCN-Pose: A Pruned and Quantized CNN for Robot Pose Estimation for Constrained Devices26 May 2022