Remote Planning and Operation of a UGV Through ROS and Commercial Mobile Networks

Sánchez-Montero, Manuel; Toscano-Moreno, Manuel; Bravo-Arrabal, Juan; Barba, Javier Serón; Vera-Ortega, Pablo; Vázquez-Martín, Ricardo; Lozano, Juan Jesús Fernández; Mandow, Anthony; García-Cerezo, Alfonso J.

doi:10.1007/978-3-031-21065-5_23

Cited by 3 publications

(5 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The other part of X-IoCA is the FIS, consisting of two components for data monitoring and processing: X-FIS, which collects data from non-ROS sensors of H2WTN for the purpose of monitoring the operation field and generating points of interest and controlling cooperative robots in response to the received information, thanks to an integrated global path planner. ROS-FIS [ 16 ], which processes and monitors information of the ROS-based sensor network, with a main computer (MPC) in each edge sharing local area network (LAN) with secondary PCs (SPC). …”

Section: Integration In a Cloud Robotics Architecturementioning

confidence: 99%

“…ROS-FIS [ 16 ], which processes and monitors information of the ROS-based sensor network, with a main computer (MPC) in each edge sharing local area network (LAN) with secondary PCs (SPC).…”

Section: Integration In a Cloud Robotics Architecturementioning

confidence: 99%

“…Biosensors are integrated into this architecture because of previous and successful applications for robot and human communication and control in disaster scenarios [ 15 , 16 , 17 , 18 , 19 ].…”

Section: Integration In a Cloud Robotics Architecturementioning

confidence: 99%

“…In previous works, we presented a mission-oriented Internet of Cooperative Agents architecture for search and rescue (SAR) missions (SAR-IoCA) [ 15 ] that integrates robotic and human agents in the field with the mission control center. SAR-IoCA allows remote control and communication [ 16 ], integrating hybrid sensor networks [ 17 ], victim close detection [ 18 ] and requests from rescuers [ 19 ]. In this work, our goal is to enable remote first responder bio-signal monitoring during SAR interventions.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human–Robot Architecture for Search and Rescue

Vera-Ortega

Vázquez-Martín

Lozano

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

The roles of emergency responders are challenging and often physically demanding, so it is essential that their duties are performed safely and effectively. In this article, we address real-time bio-signal sensor monitoring for responders in disaster scenarios. In particular, we propose the integration of a set of health monitoring sensors suitable for detecting stress, anxiety and physical fatigue in an Internet of Cooperative Agents architecture for search and rescue (SAR) missions (SAR-IoCA), which allows remote control and communication between human and robotic agents and the mission control center. With this purpose, we performed proof-of-concept experiments with a bio-signal sensor suite worn by firefighters in two high-fidelity SAR exercises. Moreover, we conducted a survey, distributed to end-users through the Fire Brigade consortium of the Provincial Council of Málaga, in order to analyze the firefighters’ opinion about biological signals monitoring while on duty. As a result of this methodology, we propose a wearable sensor suite design with the aim of providing some easy-to-wear integrated-sensor garments, which are suitable for emergency worker activity. The article offers discussion of user acceptance, performance results and learned lessons.

show abstract

Section: Integration In a Cloud Robotics Architecturementioning

confidence: 99%

Section: Integration In a Cloud Robotics Architecturementioning

confidence: 99%

Section: Integration In a Cloud Robotics Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human–Robot Architecture for Search and Rescue

Vera-Ortega

Vázquez-Martín

Lozano

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…In particular, we presented an implementation for SAR (SAR-IoCA) which was not fully integrated with ROS. In [19], we explored the application of SAR-IoCA with a remote mission control center through commercial networks.…”

Section: Introductionmentioning

confidence: 99%

Integrating ROS and Android for Rescuers in a Cloud Robotics Architecture: Application to a Casualty Evacuation Exercise

Toscano-Moreno

Bravo-Arrabal

Sánchez-Montero

et al. 2022

2022 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

View full text Add to dashboard Cite

Cloud robotics and the Internet of robotic things (IoRT) can boost the performance of human-robot cooperative teams in demanding environments (e.g., disaster response, mining, demolition, and nuclear sites) by allowing timely information sharing between agents on the field (both human and robotic) and the mission control center. In previous works, we defined an Edge/Cloud-based IoRT and communications architecture for heterogeneous multi-agent systems that was applied to search and rescue missions (SAR-IoCA). In this paper, we address the integration of a remote mission control center, which performs path planning, teleoperation and mission supervision, into a ROS network. Furthermore, we present the UMA-ROS-Android app, which allows publishing smartphone sensor data, including audio and high definition images from the rear camera, and can be used by responders for requesting a robot to the control center from a geolocalized field position. The app works up to API 32 and has been shared for the ROS community. The paper offers a case study where the proposed framework was applied to a cooperative casualty evacuation mission with professional responders and an unmanned rover with two detachable stretchers in a highfidelity exercise performed in Malaga (Spain) in June 2022.

show abstract

A Low-Cost and Lightweight Real-Time Object-Detection Method Based on UAV Remote Sensing in Transportation Systems

Liu,

Chen,

Huang

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

Accurate detection of transportation objects is pivotal for enhancing driving safety and operational efficiency. In the rapidly evolving domain of transportation systems, the utilization of unmanned aerial vehicles (UAVs) for low-altitude detection, leveraging remotely-sensed images and videos, has become increasingly vital. Addressing the growing demands for robust, real-time object-detection capabilities, this study introduces a lightweight, memory-efficient model specifically engineered for the constrained computational and power resources of UAV-embedded platforms. Incorporating the FasterNet-16 backbone, the model significantly enhances feature-processing efficiency, which is essential for real-time applications across diverse UAV operations. A novel multi-scale feature-fusion technique is employed to improve feature utilization while maintaining a compact architecture through passive integration methods. Extensive performance evaluations across various embedded platforms have demonstrated the model’s superior capabilities and robustness in real-time operations, thereby markedly advancing UAV deployment in crucial remote-sensing tasks and improving productivity and safety across multiple domains.

show abstract

Remote Planning and Operation of a UGV Through ROS and Commercial Mobile Networks

Cited by 3 publications

References 22 publications

Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human–Robot Architecture for Search and Rescue

Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human–Robot Architecture for Search and Rescue

Integrating ROS and Android for Rescuers in a Cloud Robotics Architecture: Application to a Casualty Evacuation Exercise

A Low-Cost and Lightweight Real-Time Object-Detection Method Based on UAV Remote Sensing in Transportation Systems

Contact Info

Product

Resources

About