From preparedness to action: Synthesising insights on robot usage in post-Earthquake search operations

Abstract

Human life is invaluable, and timely efforts are crucial to rescue individuals trapped under debris following an earthquake. To identify opportunities for improving post-earthquake search and rescue (SAR) robotics, we get insights through four different sources: (i) A literature review of disaster robotics and victim psychology, (ii) A public survey on earthquake awareness and their view of rescue robots, (iii) Semi-structured interviews with first responders, and (iv) Responses from GenAI chatbots which were prompted to assume the role of expert rescuers. The triangulated analysis show that there are challenges in mobility, autonomy, communication, situational awareness, and human-robot collaboration. The public respondents showed high acceptance of robot-assisted rescue and prioritised survivor detection, sensing, and communication as essential functionalities of robots. The experts expressed limitations in current equipment, the need for improved victim localisation, and interest in XR-based training and robot-assisted debris handling. The GenAI chatbots highlighted structural risk assessment, multi-sensor fusion, and supervised autonomy. Therefore, this study identifies critical robot features, outlines multi-modal interaction requirements, and highlights gaps in current SAR practice. These findings offer robot design directions for developing effective, trustworthy SAR robots, which can be integrated to future disaster-response workflows.

Keywords

Robots / Disasters / Earthquake search / Multi-modal interaction / Human-Robot interaction

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