GET THE APP

Human-robot Collaboration in Disaster Response: The Role of Rescue Robots
..

Advances in Robotics & Automation

ISSN: 2168-9695

Open Access

Commentary - (2024) Volume 13, Issue 2

Human-robot Collaboration in Disaster Response: The Role of Rescue Robots

Franin Dsouza*
*Correspondence: Franin Dsouza, Department of Automation and Control, National Taiwan University of Science and Technology, Taipei, Taiwan, Email:
Department of Automation and Control, National Taiwan University of Science and Technology, Taipei, Taiwan

Received: 27-Nov-2023, Manuscript No. Ara-23-125811; Editor assigned: 29-Nov-2023, Pre QC No. P-125811; Reviewed: 13-Dec-2023, QC No. Q-125811; Revised: 18-Dec-2023, Manuscript No. R-125811; Published: 25-Dec-2023 , DOI: 10.37421/2168-9695.2023.12.271
Citation: Dsouza, Franin. â??Human-robot Collaboration in Disaster Response: The Role of Rescue Robots.â? Adv Robot Autom 12 (2023): 271.
Copyright: © 2023 Dsouza F. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Introduction

Disasters, whether natural or man-made, pose significant challenges to emergency responders. In recent years, rescue robots have emerged as invaluable assets in disaster response efforts, enhancing the capabilities of human responders. This paper explores the crucial role of rescue robots in disaster response and the evolving landscape of human-robot collaboration. By examining technological advancements, challenges, and ethical considerations, we provide insights into the dynamic interplay between humans and robots in the face of disaster. Examine various types of rescue robots designed for disaster response. Discuss ground-based robots, aerial drones, underwater robots, and their specific roles in different scenarios. Highlight their capabilities in tasks such as search and rescue, reconnaissance, and hazard detection. Rescue robots have undergone significant advancements over the years, evolving from simple remote-controlled devices to sophisticated autonomous systems. The early 2000s witnessed the introduction of the first-generation rescue robots, primarily designed for surveillance and reconnaissance. These robots laid the foundation for the development of more advanced platforms capable of navigating challenging terrains and executing complex tasks [1].

Description

Modern rescue robots are equipped with a myriad of features that enhance their performance in disaster-stricken environments. These features include robust communication systems, advanced sensors (such as cameras, thermal imaging, and gas detectors), and ruggedized designs to withstand harsh conditions. Some robots are even capable of aerial and underwater operations, expanding their versatility in disaster response scenarios. One of the fundamental aspects of HRC in disaster response is collaborative decisionmaking. Rescue robots are designed to work alongside human responders, assisting in information gathering, risk assessment, and strategic planning. The collaboration involves real-time communication between humans and robots, allowing for seamless integration of their respective strengths [2].

Rescue robots play a pivotal role in search and rescue operations, especially in situations where human access is limited or unsafe. These robots can navigate through debris, collapsed structures, and hazardous environments, providing crucial information about the location of survivors. Additionally, some robots are equipped with payload capacities to transport essential supplies and medical equipment to those in need. Teleoperation allows human operators to control robots remotely, enabling them to navigate complex environments. Autonomy, on the other hand, empowers robots to make decisions independently based on predefined algorithms and sensor inputs. The balance between teleportation and autonomy is critical in disaster response, ensuring that humans maintain control while leveraging the efficiency of autonomous systems [3,4].

While rescue robots offer immense potential in disaster response, they also present challenges and ethical considerations. Issues such as privacy concerns, the potential misuse of technology, and the need for standardized protocols must be addressed. Striking a balance between innovation and ethical considerations is crucial for the responsible deployment of rescue robots in disaster scenarios. Effective collaboration between humans and rescue robots requires adequate training for emergency responders. Integrating rescue robots into existing emergency response protocols ensures seamless coordination during high-pressure situations. Training programs should focus on familiarizing responders with robot capabilities, communication interfaces, and troubleshooting procedures [5].

Conclusion

Human-robot Collaboration in disaster response, facilitated by the deployment of rescue robots, represents a paradigm shift in how we approach emergency situations. As technology continues to advance, the integration of robots into the disaster response ecosystem will become even more pronounced. Striking the right balance between human control and autonomous capabilities is essential to harness the full potential of rescue robots and ensure their effective use in saving lives and mitigating the impact of disasters. Present real-world case studies of successful human-robot collaboration in disaster response. Highlight instances where rescue robots played a pivotal role in saving lives, reducing risks to human responders, and improving overall mission outcomes. Discuss issues such as privacy concerns, consent, and the potential psychological impact on both victims and responders. Explore the balance between the benefits of rapid response and the ethical implications of deploying robotic technology in sensitive situations.

Acknowledgement

None.

Conflict of Interest

None.

References

  1. Rout, Deepak Kumar, Badri Narayan Subudhi, Thangaraj Veerakumar and Santanu Chaudhury. "Walsh–Hadamard-kernel-based features in particle filter framework for underwater object tracking." IEEE Trans Industr Inform 16 (2019): 5712-5722.
  2. Google Scholar, Crossref

  3. Mesquita, Daniel B., Ronaldo F. dos Santos, Douglas G. Macharet and Mario FM Campos, et al. "Fully convolutional siamese autoencoder for change detection in UAV aerial images." IEEE Geosci Remote Sens 17 (2019): 1455-1459.
  4. Google Scholar, Crossref

  5. Lee, Min-Fan Ricky and Chin-Yi Lin. "Object tracking for an autonomous unmanned surface vehicle." Machines 10 (2022): 378.
  6. Google Scholar, Crossref

  7. Zhou, Huan and Baorong Ni. "Tracking of drone flight by neural network Siamese-RPN." In 2020 6th Int Confon Eng Appl Sci and Technol (ICEAST), IEEE (2020): 1-3.
  8. Google Scholar

  9. Xiaoyue, Ji, Xiang Xiaojia and Huang Jian. "Real-time panorama stitching method for uav sensor images based on the feature matching validity prediction of grey relational analysis." In 2018 15th Int Conf Control Autom Robot Vis (ICARCV), IEEE (2018): 1454-1459.
  10. Google Scholar, Crossref, Indexed at

Google Scholar citation report
Citations: 1275

Advances in Robotics & Automation received 1275 citations as per Google Scholar report

Advances in Robotics & Automation peer review process verified at publons

Indexed In

 
arrow_upward arrow_upward