Robots in Crisis and Disaster Management: Advances in Technology, Applications, and Emerging Trends

Robotic systems can support crisis and disaster management when direct human intervention would be dangerous or delayed. This review examines 76 English-language publications indexed in Scopus and Web of Science and published from 2006 to July 2025. The studies were classified across three management domains and three Robotics Ecosystem categories. Within the reviewed sample, most publications appeared after 2015, and conference papers were the dominant document type. None of the seven reported chi-square statistics had a p-value below 0.05. Five comparisons involved overlapping labels and were therefore treated only as exploratory summaries; the descriptive counts and qualitative findings received greater interpretive weight. The reviewed literature suggests that no single robotic platform meets the demands of every disaster scenario. UAVs are useful for surveying, mapping, and observing inaccessible areas, while ground and specialized robots support close inspection, environmental sensing, and work in confined or unstable environments. Multi-robot systems can extend mission coverage but also increase the demands on communication, coordination, data fusion, task allocation, and operator supervision. Many of the included solutions were evaluated only in simulations, prototype demonstrations, or short experiments. Recurrent limitations concerned field validation, perception, localization, real-time processing, communication, autonomy, interoperability, reliability, energy use, and human–robot collaboration. Future studies should test complete systems in repeatable field exercises and retain human supervision over safety-critical decisions.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2026-10-14
DOI
https://doi.org/10.3390/s26206518
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robots in Crisis and Disaster Management: Advances in Technology, Applications, and Emerging Trends

Jacek Łukasz Wilk-Jakubowski, Grzegorz Wilk-Jakubowski, Daniel Kaczmarski
Sensors
Robotics and Automated Systems
article

Robots in Crisis and Disaster Management: Advances in Technology, Applications, and Emerging Trends

Jacek Łukasz Wilk-Jakubowski, Grzegorz Wilk-Jakubowski, Daniel Kaczmarski
article en

Abstract

Robotic systems can support crisis and disaster management when direct human intervention would be dangerous or delayed. This review examines 76 English-language publications indexed in Scopus and Web of Science and published from 2006 to July 2025. The studies were classified across three management domains and three Robotics Ecosystem categories. Within the reviewed sample, most publications appeared after 2015, and conference papers were the dominant document type. None of the seven reported chi-square statistics had a p-value below 0.05. Five comparisons involved overlapping labels and were therefore treated only as exploratory summaries; the descriptive counts and qualitative findings received greater interpretive weight. The reviewed literature suggests that no single robotic platform meets the demands of every disaster scenario. UAVs are useful for surveying, mapping, and observing inaccessible areas, while ground and specialized robots support close inspection, environmental sensing, and work in confined or unstable environments. Multi-robot systems can extend mission coverage but also increase the demands on communication, coordination, data fusion, task allocation, and operator supervision. Many of the included solutions were evaluated only in simulations, prototype demonstrations, or short experiments. Recurrent limitations concerned field validation, perception, localization, real-time processing, communication, autonomy, interoperability, reliability, energy use, and human–robot collaboration. Future studies should test complete systems in repeatable field exercises and retain human supervision over safety-critical decisions.

SensorsVol. 26(20)
Kielce University of Technology (PL)
Openalex Percentile: Top 17%
Robotics and Automated Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.