RescueFlex: A Modular Intelligent Rescue Robot System for Complex Disaster Scenarios

This study presents RescueFlex, a modular intelligent rescue and transport robot system designed to address key challenges in complex disaster rescue scenarios. Based on a quadruped robot platform, the system integrates multi-robot collaboration, modular design, and autonomous navigation technologies, incorporating thermal imaging, search and rescue, material transport, and medical evacuation functional modules. The research context stems from rescue needs in disaster-prone regions, particularly in countries severely affected by disasters like China, where approximately 90% of disaster deaths in remote areas are caused by delayed rescue operations, with a critical rescue window of only 72 hours. Traditional rescue methods show significant limitations when facing complex environments: first, time inefficiency leads to limited coverage within the rescue window; second, poor environmental adaptability results in high equipment failure rates in extreme conditions; third, information processing delays are closely related to rescue failures and insufficient information sharing. The RescueFlex system addresses these challenges through user-centered design methods and human-computer interaction innovations. The system adopts a "user-centered" design philosophy, combining contextual design and systematic innovation approaches through in-depth user research, scenario analysis, and iterative design to create a highly modular and adaptive rescue system. The system architecture includes hardware systems (core navigation unit, functional modules, sensing systems), software systems (autonomous navigation, multi-robot collaboration, task planning), and interaction systems (intuitive interfaces, multimodal interaction). This research provides innovative solutions and design paradigms for the disaster rescue field from human-computer interaction and design perspectives, with significant implications for improving rescue efficiency and ensuring personnel safety.

Authors

Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006248
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

RescueFlex: A Modular Intelligent Rescue Robot System for Complex Disaster Scenarios

Zhixin Cai
AHFE international
Robotic Path Planning Algorithms
article

RescueFlex: A Modular Intelligent Rescue Robot System for Complex Disaster Scenarios

Zhixin Cai
article en

Abstract

This study presents RescueFlex, a modular intelligent rescue and transport robot system designed to address key challenges in complex disaster rescue scenarios. Based on a quadruped robot platform, the system integrates multi-robot collaboration, modular design, and autonomous navigation technologies, incorporating thermal imaging, search and rescue, material transport, and medical evacuation functional modules. The research context stems from rescue needs in disaster-prone regions, particularly in countries severely affected by disasters like China, where approximately 90% of disaster deaths in remote areas are caused by delayed rescue operations, with a critical rescue window of only 72 hours. Traditional rescue methods show significant limitations when facing complex environments: first, time inefficiency leads to limited coverage within the rescue window; second, poor environmental adaptability results in high equipment failure rates in extreme conditions; third, information processing delays are closely related to rescue failures and insufficient information sharing. The RescueFlex system addresses these challenges through user-centered design methods and human-computer interaction innovations. The system adopts a "user-centered" design philosophy, combining contextual design and systematic innovation approaches through in-depth user research, scenario analysis, and iterative design to create a highly modular and adaptive rescue system. The system architecture includes hardware systems (core navigation unit, functional modules, sensing systems), software systems (autonomous navigation, multi-robot collaboration, task planning), and interaction systems (intuitive interfaces, multimodal interaction). This research provides innovative solutions and design paradigms for the disaster rescue field from human-computer interaction and design perspectives, with significant implications for improving rescue efficiency and ensuring personnel safety.

AHFE internationalVol. 195
Openalex Percentile: Top 87%
Robotic Path Planning Algorithms
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RescueFlex: A Modular Intelligent Rescue Robot System for Complex Disaster Scenarios — Zhixin Cai · AHFE international (2025) | TGRS Research Map | TGRS