SAR4.0 - Leapfrogging to a New Paradigm in Cooperative Human-Robot Cyber-physical Systems for Search and Rescue

 

Project Info

• Title: "SAR 4.0:  Leapfrogging to a New Paradigm in Cooperative Human-Robot Cyber-physical Systems for Search and Rescue ".
• Reference: PID2021-122944OB-I00. Ministerio de Ciencia e Innovación. Proyectos de Generación del Conocimiento 2021.
• Principal Investigators: Alfonso José García Cerezo y Antonio Mandow Andaluz
• Universidad de Málaga, Institute for Mechatronics Engineering and Cyber-Physical Systems (IMECH.UMA).
• January 2022-December 2024.

Disaster robotics, such unmanned aerial (UAV) and ground (UGV) vehicles, are increasingly being considered as trustworthy technological aids in search and rescue (SAR) missions.  At this point, a paradigm shift of disaster robotics towards data-driven distributed cyber-physical systems, in line with the principles of Industry 4.0, is crucial for providing rescuers with a comprehensive perception of disaster scenarios, their surroundings, the understanding of their meaning, and a projection of their evolution in the immediate future. 

The mission of the SAR4.0 project is to develop new collaborative SAR support technology where heterogeneous robotic teams, sensor networks, communication systems and deployed artificial intelligence (AI) produce seamless, transparent, fluid, and adaptive support to the responders with the ultimate goals of optimizing SAR efficiency and minimizing mission-associated risks.  The early adoption of cutting-edge advances in AI and communications -like the Internet of robotic things (IoRT), multi-access edge computing (MEC), ad hoc networks, and pervasive sensing- is decisive for achieving interconnectivity of heterogeneous systems, real-time coordination of robot and human teams, timely interpretation of massive multi-modal data, and adaptability to diverse environments and sorts of natural and human-made disasters.

The development of SAR4.0 will provide comprehensive contributions to five major research challenges imposed by the demanding environmental conditions of disaster scenarios for human-robot cooperation: 1) Developing specific interoperatibility requirements will increase adaptability to specific SAR mission specifications, reduce integration risks and implementation time, favor rapid deployment, and reduce complexity for all actors (from end-users to maintenance teams). 2) The definition of an IoRT distributed architecture will provide a framework to integrate all the elements in a SAR mission, including heterogeneous mobile robots (UGVs and UAVs), wireless sensor networks, and remote (i.e., edge, and/or cloud) computing based on either commercial or ad hoc communication networks. Third, achieving a smart space with ambient intelligence in a disaster scenario will involve a deployable hybrid sensor network consisting of fixed and mobile nodes, special mechanisms for sensor deployment, telepresence, multi-modal object recognition for victim detection and scene understanding, sensors for victim monitorization and diagnosis, and wearable biometric sensors for monitoring responder stress levels and activity. 4) Novel robot intelligence methods for SAR will include a strategic mission control system, trajectory planning algorithms for realistic environmental conditions, strategies for flock or swarm of heterogeneous robots, and collaborative 3D localization and mapping.  5) The implementation of the SAR4.0 system will be tested and validated in realistic field exercises with professional rescue teams, providing valuable applicability insights, open datasets for the international disaster robotics community, and dissemination opportunities towards emergency response stakeholders.

 

> Video Gallery

> Public Datasets

> Collaborations and agreements with other research institutions

> Internationalization activities

> Publications

 

Video Gallery

Link to UMA Robotics & Mechatronics YouTube Channel.

 

Public Datasets

•  UMA-SAR Dataset A full description of the open dataset is given in the IJRR article: https://doi.org/10.1177/02783649211004959. 
• Natural Environment Gazebo Simulation of a Unmanned Ground Vehicle (NEGS-UGV) Dataset.  A full description of the dataset is given in the MDPI Sensors article: https://doi.org/10.3390/s22155599

 

 

Collaborations and agreements with other research institutions

Collaborations with international and national research groups directly related with the project.

 INTERNATIONAL

NATIONAL

 

Internationalization activities and collaborations related with the project.  

 

Publications

Journal Articles

Castellano-Quero M., Castillo-López M., Fernández-Madrigal J.-A., Arévalo-Espejo V., Voos H., García-Cerezo, A. 
A multidimensional Bayesian architecture for real-time anomaly detection and recovery in mobile robot sensory systems. 
(2023) Engineering Applications of Artificial Intelligence, 125, art. no. 106673. OPEN ACCESS  
DOI: https://www.doi.org/10.1016/j.engappai.2023.106673 

Pastor, F., Ruiz-Ruiz, F.J., Gomez-De-Gabriel, J.M., Garcia-Cerezo, A.J. 
Autonomous Wristband Placement in a Moving Hand for Victims in Search and Rescue Scenarios With a Mobile Manipulator   
(2023) IEEE Robotics and Automation Letters, 7, (4), pp. 11871-11878, DOI: https://www.doi.org/10.1109/LRA.2022.3208349  

Toscano-Moreno, M., Mandow, A., Martínez, M.A., García-Cerezo, A.
DEM-AIA: Asymmetric inclination-aware trajectory planner for off-road vehicles with digital elevation models
(2023) Engineering Applications of Artificial Intelligence, 121, art. no. 105976. OPEN ACCESS

DOI: https://www.doi.org/10.1016/j.engappai.2023.105976

Sánchez, M., Morales, J., Martínez, J.L.
Reinforcement and Curriculum Learning for Off-Road Navigation of an UGV with a 3D LiDAR
(2023) Sensors, 23 (6), art. no. 3239. OPEN ACCESS
DOI: https://www.doi.org/10.3390/s23063239 

Godoy-Calvo, J., Lin-Yang, D., Vázquez-Martín, R., García-Cerezo, A.
Dynamic entropy-based method for exploring frontiers in unknown environments [Exploración dinámica de fronteras en entornos desconocidos basada en la entropía]. 
(2023) RIAI - Revista Iberoamericana de Automatica e Informatica Industrial, 20 (2), pp. 213-223. OPEN ACCESS
DOI: https://www.doi.org/10.4995/riai.2023.18740
 
Martinez, J.L., Morales, J., Garcia, J.M., Garcia-Cerezo, A.
Analysis of Tread ICRs for Wheeled Skid-Steer Vehicles on Inclined Terrain
(2023) IEEE Access, 11, pp. 547-555. OPEN ACCESS
DOI: https://www.doi.org/10.1109/ACCESS.2022.3232954

Vera-Ortega, P., Vázquez-Martín, R., Fernandez-Lozano, J.J., García-Cerezo, A., Mandow, A.
Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human–Robot Architecture for Search and Rescue
(2023) Sensors, 23 (1), art. no. 49. OPEN ACCESS
DOI: https://www.doi.org/10.3390/s23010049

Pastor, F., Lin-Yang, D.-H., Gómez-de-Gabriel, J.M., García-Cerezo, A.J.
Dataset with Tactile and Kinesthetic Information from a Human Forearm and Its Application to Deep Learning
(2022) Sensors, 22 (22), art. no. 8752. OPEN ACCESS
DOI: https://www.doi.org/10.3390/s22228752
 
Pastor, F., Ruiz-Ruiz, F.J., Gomez-De-Gabriel, J.M., Garcia-Cerezo, A.J.
Autonomous Wristband Placement in a Moving Hand for Victims in Search and Rescue Scenarios With a Mobile Manipulator
(2022) IEEE Robotics and Automation Letters, 7 (4), pp. 11871-11878. 
DOI: https://www.doi.org/10.1109/LRA.2022.3208349
 
Sánchez, M., Morales, J., Martínez, J.L., Fernández-Lozano, J.J., García-Cerezo, A.
Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations
(2022) Sensors, 22 (15), art. no. 5599. OPEN ACCESS
DOI: https://www.doi.org/10.3390/s22155599
 
Cantizani-Estepa, J., Bravo-Arrabal, J., Fernández-Lozano, J.J., Fortes, S., Barco, R., García-Cerezo, A., Mandow, A.
Bluetooth Low Energy for Close Detection in Search and Rescue Missions with Robotic Platforms: An Experimental Evaluation
(2022) IEEE Access, 10, pp. 106169-106179. OPEN ACCESS
DOI: https://www.doi.org/10.1109/ACCESS.2022.3204272

Bravo-Arrabal, J., Zambrana, P., Fernandez-Lozano, J.J., Gomez-Ruiz, J.A., Barba, J.S., Garcia-Cerezo, A.
Realistic Deployment of Hybrid Wireless Sensor Networks Based on ZigBee and LoRa for Search and Rescue Applications
(2022) IEEE Access, 10, pp. 64618-64637. OPEN ACCESS
DOI: https://www.doi.org/10.1109/ACCESS.2022.318313

 

Other Publications

Fernández Lozano, J.J., Mandow, A., Miranda Páez, J., Trillo Legaz, J., Ravina Vergara, J. M., García Cerezo, A.J.
Diseñar lo inesperado: experiencias en la realización de experimentos de campo realistas en robótica para emergencias.
(2023) Jornadas Nacionales de Robótica y Bioingeniería 2023, pp. 41-48.
https://doi.org/10.20868/UPM.book.74896
 
Sánchez-Montero, M., Toscano-Moreno, M., Bravo-Arrabal, J., Serón Barba, J., Vera-Ortega, P., Vázquez-Martín, R., Fernandez-Lozano, J.J., Mandow, A., García-Cerezo, A.
Remote Planning and Operation of a UGV Through ROS and Commercial Mobile Networks
(2023) Lecture Notes in Networks and Systems, 589 LNNS, pp. 271-282. 
DOI: https://www.doi.org/10.1007/978-3-031-21065-5_23
 
Toscano-Moreno, M., Bravo-Arrabal, J., Sanchez-Montero, M., Barba, J.S., Vazquez-Martin, R., Fernandez-Lozano, J.J., Mandow, A., Garcia-Cerezo, A.
Integrating ROS and Android for Rescuers in a Cloud Robotics Architecture: Application to a Casualty Evacuation Exercise
(2022) SSRR 2022 - IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 270-276.
DOI: https://www.doi.org/10.1109/SSRR56537.2022.10018629
 
González Centeno, A., Vázquez-Martín, R., Mandow, A., García-Cerezo, A., 
Detección de partes del cuerpo en imágenes multimodales de búsqueda y rescate.
(2022) Jornadas de Robótica, Educación y Bioingeniería 2022, Málaga, pp. 161-168.