PRE2022 3 Group2

Group members

Name	Student Number	Study
Clinton Emok	1415115	BCS
Richard Farla	1420380	BCS
Yash Israni	1415883	BCS
Tessa de Jong	1498312	BPT
Kaj Scholer	1567942	BME
Pepijn Tennebroek	1470221	BPT

Abstract

The use of robotics in disaster response operations has gained significant attention in recent years. In particular, low-cost vine robots have been proposed as a promising technology for search and rescue missions in urban areas affected by earthquakes. Vine robots are small, flexible and lightweight robots that can navigate through tight spaces and confined areas, making them ideal for searching collapsed buildings for survivors. They are also relatively cheaper and easier to assemble than other current search and rescue robots. However, vine robots have not been implemented into real-life search and rescue missions due to various complications. These complications have been evaluated and some solutions have been provided with regards to the sensors being used, as well as the localization and path planning of the vine robot. This paper only acts as an aid to support future implementation of vine robots into search and rescue missions.

Introduction and project goals

Earthquakes are one of the most devastating natural disasters that can occur in urban areas, leading to significant damage to infrastructure, loss of life and displacement of communities. In recent years, search and rescue operations have become increasingly important in the aftermath of earthquakes. These operations aim to locate victims trapped under collapsed buildings and provide them with the necessary medical care and assistance. However, these operations can be challenging due to the complexity and dangers associated with navigating through the rubble of damaged buildings.

To address these challenges, low-cost vine robots have emerged as a promising technology for search and rescue operations in urban areas affected by earthquakes. Vine robot are small lightweight and flexible robots that can crawl slither or climb through tight spaces and confined areas making them ideal for searching collapse buildings for survivors. these robots can be equipped with camera sensors and other devices that can aid in localization of victims.

The usage of low-cost find robots in earthquake response after it has the potential to significantly improve the efficiency and effectiveness of search and rescue operations, as well as reduce the risk to human rescuers. this paper provides an overview of the usage of low-cost van robots in the localization of victims of earthquakes that lead to infrastructure damage specifically in urban areas.

This paper presents a comprehensive review of the literature on the usage of low-cost vine robot in earthquake response efforts. The paper provides an overview of the design and capabilities of vine robots, highlighting their potential advantages over traditional search and rescue methods. This paper also discusses the challenges associated with the usage of vine robots, such as limited battery life, difficulties in controlling the robot in complex environments and the need for specialized training for operators.

To support the analysis, this paper draws on case studies of the deployment of vine robot in earthquake disasters, including the 2010 Haiti earthquake, the 2017 Mexico City earthquake and the 2019 Albania earthquake. The case studies serve to illustrate the effectiveness of vine robots in localizing victims as well as the challenges rescue teams face by utilizing this technology.

The research questions addressed in this paper include:

What are the design and capabilities of low-cost van robots and how do they differ from 4-0 search and rescue methods?
What are the potential advantages and challenges associated with the usage of low-cost van robots in earthquake response efforts?
How have vine robots been deployed in recent earthquake disasters and what has their impact on search and rescue operations been?
What are the future prospects of low-cost vine robots in earthquake response efforts?

Extra Content for Introduction (to be adjusted...)

“Two large earthquakes struck the southeastern region of Turkey near the border with Syria on Monday, killing thousands and toppling residential buildings across the region.” (AJLabs, 2023) The earthquakes were both above 7.5 on the Richter scale, which caused buildings to be displaced from foundations with people still in them. Some people survived the fall when a building collapsed, but were trapped in all of the rubble.

After earthquakes of high magnitude, it is necessary to rescue survivors from destroyed buildings as fast as possible. Namely, the chances of finding people alive in rubble fade with each passing day. However, it can be hard for human rescuers and rescue dogs to reach these areas due to the dangers of collapsing buildings. Therefore, the usage of robotics can be introduced in these rescue operations. In this report, it is investigated how the usage of vine robotics could improve localizing alive people after earthquakes of high magnitude. Furthermore, it is looked into how the vine robot can prolong survivors’ lives. This would hopefully increase the number of people that are saved after such a natural disaster. In order to do this, literature research is conducted and a simulation and prototype will be created.

For this project, we will focus on urban search and rescue. This means as stated in Wikipedia: “a type of technical rescue operation that involves the location, extrication, and initial medical stabilization of victims trapped in an urban area, namely structural collapse due to natural disasters, war, terrorism or accidents, mines and collapsed trenches.” Our scope will be the urban area after an earthquake, so we will deal with the collapsed buildings and structures that arise from them. In the scenario, where our vine robot will operate, will not be any fire or water which the robot has to take into account

Project planning and deliverables

Week	Milestones
Week 1	Topic, problem identification, planning, state-of-the-art literature research
Week 2	Further literature study, user analysis, MoSCoW, CAD modelling, research for simulation possibility, research/order electronics
Week 3	Further literature study, complete CAD modelling, start simulation, research localization methods, research sensors used
Week 4	Work on prototype, work on simulation
Week 5	Work on prototype, finalize simulation
Week 6	Finalize prototype, gather results from testing
Week 7	Evaluate results and conclusion
Week 8	Complete wiki and presentation

Who is doing what?

Names	Tasks
Clinton Emok	Sensors and Localization
Richard Farla	Simulation
Yash Israni	Simulation
Tessa de Jong	Literature Research
Kaj Scholer	Sensors and Localization
Pepijn Tennebroek	Literature Research

State-of-the-art literature (clean up sources here after completing table)

Existing rescue robots

The Current State and Future Outlook of Rescue Robotics (to be completed....)

There are multiple state-of-the-art and future outlook of rescue robots. Currently, full autonomy in real-world rescue situations is difficult to apply in real cases. There is a strong preference for semiautonomous behaviors, rather than full manual control.

Technology in rescue robots

Specially Designed Multi-Functional Search And Rescue Robot

In this paper, a sensor-based multi-functional search and rescue robot system for use in emergency situations is designed. They provide an insight on the various sensors that are included in this robot system, which are the following: servo motor, USB camera, DC motor, motor driver module, stepper motor, Darlington transistor arrays, ultrasonic sensor, Raspberry Pi 3 model B+ and Arduino mega. This robot system can search humans in ruined areas and send the collected data to a web server, which is then able to video steam in real-time.

Life Signs Detector Using a Drone in Disaster Zones

A novel computer vision system can be utilized on drones to detect signs of life in dangerous areas. From the results, it was proven that motion-based breathing detection from an aerial platform is possible with a high certainty. The system successfully distinguished between humans and mannequins in daylight using human operator and a powerful PC equipped with MATLAB.

Search and Rescue System for Alive Human Detection by Semi-Autonomous Mobile Rescue Robot

This paper provided a low cost human detection robot for rescue missions in extreme situations. Various system block diagrams and flowcharts were created to show the functionality of the robot. A PIR sensor and IP camera was used, which detects humans by their radiated infrared wave and to confirm their existence. Compared to over urban search and rescue robots, these sensors are cheap and easily available.

Legged Robots That Balance

Presents implications for theories of human motor control. It lays fundamental groundwork in legged locomotion, one of the least developed areas of robotics, addressing the possibility of building useful legged robots that run and balance.

An Overview of Legged Robots

This paper presented the evolution and the state-of-the- art in the area of legged locomotion systems. The different possibilities for mobile robots are discussed, such as the case of artificial legged locomotion systems, where their advantages and limitations are explored.

Rescue robots in action

Disaster Robotics

This book provides an overview of rescue robotics in the context of emergency informatics. It also provides a chronological summary and a formal analysis of the thirty-four documented deployments of robots to disasters. It acts as a definitive guide to the theory and practice of previous disaster robotics, and serves as an introduction into this field.

Title of paper	Reference	Reader
Robotically negotiating stairs	(Is this a good source?)	Richard
Specially Designed Multi-Functional Search And Rescue Robot	Nosirov, K., Shakhobiddinov, A., Arabboev, M., Begmatov, S., & Togaev, O. (2020). Specially Designed Multi-Functional Search And Rescue Robot. Bulletin of TUIT: Management and Communication Technologies: Vol. 2, Article 1.	Richard
The current state and future outlook of rescue robotics	Delmerico, J., Mintchev, S., Giusti, A., Gromov, B., Melo, K., Horvat, T., Cadena, C., Hutter, M., Ijspeert, A., Floreano, D., Gambardella, L. M., Siegwart, R., & Scaramuzza, D. (2019). The current state and future outlook of rescue robotics. Journal of Field Robotics, 36, 7 (pp. 1171-1191). https://doi.org/10.1002/rob.21887	Richard
Life Signs Detector Using a Drone in Disaster Zones		Richard
Search and rescue system for alive human detection by semi-autonomous mobile rescue robot		Richard

Robotic Urban Search and Rescue: A Survey from the Control Perspective		Yash
Robots Gear Up For Disaster Response		Yash
Application of robot technologies to the disaster sites		Yash
Emergency response by robots to Fukushima‐Daiichi accident: summary and lessons learned		Yash
Utilization of Robot Systems in Disaster Sites of the Great Eastern Japan Earthquake	Matsuno, F., Sato, N., Kon, K., Igarashi, H., Kimura, T., & Murphy, R. (2013). Utilization of Robot Systems in Disaster Sites of the Great Eastern Japan Earthquake. Springer Tracts in Advanced Robotics, 1–17. https://doi.org/10.1007/978-3-642-40686-7_1	Yash

Multimodality robotic systems: Integrated combined legged-aerial mobility for subterranean search-and-rescue	Lindqvist, B., Karlsson, S., Koval, A., Tevetzidis, I., Haluška, J., Kanellakis, C., Agha-mohammadi, A. A., & Nikolakopoulos, G. (2022). Multimodality robotic systems: Integrated combined legged-aerial mobility for subterranean search-and-rescue. Robotics and Autonomous Systems, 154, 104134. https://doi.org/10.1016/j.robot.2022.104134	Tessa
Rescue robotics: DDT project on robots and systems for urban search and rescue	Tadokoro, S. (Ed.). (2009). Rescue robotics: DDT project on robots and systems for urban search and rescue. Springer Science & Business Media.	Tessa
The EU-ICARUS project: Developing assistive robotic tools for search and rescue operations	De Cubber, G., Doroftei, D., Serrano, D., Chintamani, K., Sabino, R., & Ourevitch, S. (2013, October). The EU-ICARUS project: developing assistive robotic tools for search and rescue operations. In 2013 IEEE international symposium on safety, security, and rescue robotics (SSRR) (pp. 1-4). IEEE.	Tessa
Drone-assisted disaster management: Finding victims via infrared camera and lidar sensor fusion.	Lee, S., Har, D., & Kum, D. (2016, December). Drone-assisted disaster management: Finding victims via infrared camera and lidar sensor fusion. In 2016 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE) (pp. 84-89). IEEE.	Tessa

Boston Dynamics’ Spot Is Helping Chernobyl Move Towards Safe Decommissioning.		Kaj
Rescue Robots for the Urban Earthquake Environment \| Disaster Medicine and Public Health Preparedness		Kaj
Review Paper on Search and Rescue Robot for Victims of Earthquake and Natural Calamities.		Kaj
Detecting Earthquake Victims Through Walls		Kaj
Land-Mobile Robots for Rescue and Search: A Technological and Systematic Review		Kaj

Active scope camera for urban search and rescue		Pepijn
Use of active scope camera in the Kumamoto Earthquake to investigate collapsed houses		Pepijn
The design of telescopic universal joint for earthquake rescue robot		Pepijn
Design of four-arm four-crawler disaster response robot OCTOPUS		Pepijn
Disaster response and recovery from the perspective of robotics		Pepijn

Legged Robots That Balance	M. H. Raibert and E. R. Tello, "Legged Robots That Balance," in IEEE Expert, vol. 1, no. 4, pp. 89-89, Nov. 1986, doi: 10.1109/MEX.1986.4307016.	Clinton
An Overview of Legged Robots	Tenreiro Machado, José & Silva, Manuel. (2006). An Overview of Legged Robots.	Clinton
Disaster Robotics	Murphy, R. R. (2017). Disaster Robotics. Amsterdam University Press	Clinton
Designing, developing, and deploying systems to support human–robot teams in disaster response	Geert Kruijff, Ivana Kruijff-Korbayová, Shanker Keshavdas, Benoit Larochelle, Miroslav Janíček, et al.. Designing, developing, and deploying systems to support human–robot teams in disaster response. Advanced Robotics, 2014, 28 (23), pp.1547–1570. ff10.1080/01691864.2014.985335	Clinton
Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities	Sanfilippo F, Azpiazu J, Marafioti G, Transeth AA, Stavdahl Ø, Liljebäck P. Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities ^†. Applied Sciences. 2017; 7(4):336. https://doi.org/10.3390/app7040336	Clinton

Clinton

Raibert, M. H. (2000). Legged Robots That Balance. MIT Press. Presents implications for theories of human motor control. It lays fundamental groundwork in legged locomotion, one of the least developed areas of robotics, addressing the possibility of building useful legged robots that run and balance.
Tenreiro Machado, J. A., & Silva, M. F. (2006). An Overview of Legged Robots. An Overview of Legged Robots. Presents the evolution and the state-of-the- art in the area of legged locomotion systems. In a first phase different possibilities for mobile robots are discussed, namely the case of artificial legged locomotion systems, while emphasizing their advantages and limitations.
Murphy, R. R. (2017). Disaster Robotics. Amsterdam University Press. After an overview of rescue robotics in the context of emergency informatics, the book provides a chronological summary and formal analysis of the thirty-four documented deployments of robots to disasters.
Kruijff, G. M., Kruijff-Korbayová, I., Keshavdas, S., Larochelle, B., Janíček, M., Colas, F., Liu, M., Pomerleau, F., Siegwart, R., N., Looije, R., Smets, N. J. J. M., Mioch, T., Van Diggelen, J., Pirri, F., Gianni, M., Ferri, F., Menna, M., Worst, R., . . . Hlaváč, V. (2014). Designing, developing, and deploying systems to support human–robot teams in disaster response. Advanced Robotics, 28(23), 1547–1570. https://doi.org/10.1080/01691864.2014.985335. Designing, developing, and deploying systems to support human–robot teams in disaster response
Sanfilippo F, Azpiazu J, Marafioti G, Transeth AA, Stavdahl Ø, Liljebäck P. Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities †. Applied Sciences. 2017; 7(4):336. https://doi.org/10.3390/app7040336. Snake robots could be fitted with sensors and transport tools to hazardous or confined areas that other robots and humans are unable to access. They expanded the description for increasing the level of autonomy within three main robot technology areas: guidance, navigation, and control.

Richard

Boston Dynamics, Inc. (2019). Robotically negotiating stairs (Patent Nr. 11,548,151). Justia. https://patents.justia.com/patent/11548151 A method for negotiating stairs includes receiving image data about a robot maneuvering in an environment with stairs with one or two legs. Closely related to traversing terrain that is riddled with fallen objects and debris
Specially Designed Multi-Functional Search And Rescue Robot. (2020). Bulletin of TUIT: Management and Communication Technologies. https://doi.org/10.51348/tuitmct211 In this paper, they design a sensor-based multi-functional search and rescue robot system for use in emergency situations.
Delmerico, J., Mintchev, S., Giusti, A., Gromov, B., Melo, K., Horvat, T., Cadena, C., Hutter, M., Ijspeert, A., Floreano, D., Gambardella, L. M., Siegwart, R., & Scaramuzza, D. (2019). The current state and future outlook of rescue robotics. Journal of Field Robotics, 36(7), 1171–1191. https://doi.org/10.1002/rob.21887 State-of-the-art and future outlook of rescue robots. Full autonomy in real-world rescue situations is currently difficult to apply in real cases. There is a strong preference for semiautonomous behaviors, rather than full manual control.
Al-Naji, A., Perera, A. G., Mohammed, S. L., & Chahl, J. (2019). Life Signs Detector Using a Drone in Disaster Zones. Remote Sensing, 11(20), 2441. https://doi.org/10.3390/rs11202441 Drones to detect signs of life in dangerous areas.
Uddin, Z., & Islam, M. (2016). Search and rescue system for alive human detection by semi-autonomous mobile rescue robot. 2016 International Conference on Innovations in Science, Engineering and Technology (ICISET). https://doi.org/10.1109/iciset.2016.7856489 Robot for alive human detection in unreachable points of a disaster area. Many people died by trapping under debris as their presence cannot detect by the rescue team. Joystick and RF technology is used to control the semi-autonomous robot and communicate with control point.

Yash

Liu, Y., Nejat, G. Robotic Urban Search and Rescue: A Survey from the Control Perspective. J Intell Robot Syst 72, 147–165 (2013). https://doi.org/10.1007/s10846-013-9822-x This paper provides a detailed overview of developments in the exciting and challenging area of robotic control for USAR environments. Developing low-level controllers for rescue robot autonomy, task sharing of multiple tasks between operator and robot, high-level control schemes that have been designed for multi-robot rescue teams.
Anthes, Gary. Robots Gear Up for Disaster Response. Communications of the ACM (2010): 15, 16. Web. 10 Oct. 2012 Brilliant robotic technology exists but it needs to be integrated into complete, robust systems, andsensors and other components must bemade smaller, stronger, and cheaper.
Osumi, H. (2014). Application of robot technologies to the disaster sites. Report of JSME Research Committee on the Great East Japan Earthquake Disaster, 58-74. During the Great East Japan Earthquake disaster, Japanese rescue robots were used for actual disaster sites for the first time. Due to the radioactivity and debris the tele-operation function and the ability to move on debris was needed.
Matsuno, F., Sato, N., Kon, K., Igarashi, H., Kimura, T., Murphy, R. (2014). Utilization of Robot Systems in Disaster Sites of the Great Eastern Japan Earthquake. In: Yoshida, K., Tadokoro, S. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 92. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40686-7_. Three lessons were learned after deploying robots from recovery operations: Rescue robots are valuable for both economic and victim recovery, not just response. Disaster robots need to be optimized for the unique missions and stakeholder needs. Human-robot interaction remains a challenge.
Kawatsuma, S., Fukushima, M., & Okada, T. (2013). Emergency response by robots to Fukushima-Daiichi accident: summary and lessons learned. Journal of Field Robotics, 30(1), 44-63. doi: 10.1002/rob.21416 Many lessons had been learned from the experiences on robots' emergency response to the accident; organization and operation scheme, and systemization were major lessons learned.

Tessa

Matsuno, F., Sato, N., Kon, K., Igarashi, H., Kimura, T., & Murphy, R. (2013). Utilization of Robot Systems in Disaster Sites of the Great Eastern Japan Earthquake. Springer Tracts in Advanced Robotics, 1–17. https://doi.org/10.1007/978-3-642-40686-7_1 --> After the Great Eastern Japan earthquake in 2011, researchers investigated how robots could be used in disaster sites. They found that disaster robots should at least be “easy to transport, quick to set up, reliable and record the data for later viewing” (Matsuno et al., 2013). The robots could be further optimized with GPS mapping, station-keeping abilities, and image enhancement.
Quote from the blog of the Dutch search team in Turkey: "We merken dat de honden vermoeid raken door de vele inzetten." (Urban Search and Rescue Team, 2023). This implements that dogs are getting tired after searching for several days.

Kaj

Ackerman, E. (2023). Boston Dynamics’ Spot Is Helping Chernobyl Move Towards Safe Decommissioning. IEEE Spectrum. https://spectrum.ieee.org/boston-dynamics-spot-chernobyl
Li, F. (n.d.). Rescue Robots for the Urban Earthquake Environment | Disaster Medicine and Public Health Preparedness. Cambridge Core. https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/abs/rescue-robots-for-the-urban-earthquake-environment/AE4E401B0D089C78EDB0DB635768D93A
International Journal IJRITCC, & Kharad, S. (2016, September 4). Review Paper on Search and Rescue Robot for Victims of Earthquake and Natural Calamities. https://www.academia.edu/28254631/Review_Paper_on_Search_and_Rescue_Robot_for_Victims_of_Earthquake_and_Natural_Calamities
Hampson, M. (2022, November 22). Detecting Earthquake Victims Through Walls. IEEE Spectrum. https://spectrum.ieee.org/dopppler-radar-detects-breath
D. Huamanchahua, K. Aubert, M. Rivas, E. Guerrero, L. Kodaka and D. Guevara, "Land-Mobile Robots for Rescue and Search: A Technological and Systematic Review," 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), Toronto, ON, Canada, 2022, pp. 1-6, doi: 10.1109/IEMTRONICS55184.2022.9795829.

Pepijn

K. Hatazaki, M. Konyo, K. Isaki, S. Tadokoro and F. Takemura, "Active scope camera for urban search and rescue," 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA, 2007, pp. 2596-2602, doi: 10.1109/IROS.2007.4399386. This paper presents the design and implementation of an Active Scope Camera (ASC) for urban search and rescue operations. The ASC is a compact and lightweight device that can be used to explore confined spaces and provide visual information to rescuers.
Y. Ambe et al., "Use of active scope camera in the Kumamoto Earthquake to investigate collapsed houses," 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Lausanne, Switzerland, 2016, pp. 21-27, doi: 10.1109/SSRR.2016.7784272. This paper describes the application of the Active Scope Camera (ASC) in the aftermath of the Kumamoto earthquake in Japan in 2016. It is described how the ASC was able to provide critical information to the rescue teams, leading to the successful rescue of several trapped occupants. The paper highlights the importance of using advanced imaging technologies, such as the ASC, in urban search and rescue operations to enhance the effectiveness and safety of rescue workers.
L. Zhao, G. Sun, W. Li and H. Zhang, "The design of telescopic universal joint for earthquake rescue robot," 2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), Tokyo, Japan, 2016, pp. 62-66, doi: 10.1109/ACIRS.2016.7556189. --> The paper presents a transmission system including the telescopic universal joint used for the snake like search and rescue robot. The paper highlights the importance of designing flexible and adaptable robotic systems for use in rescue operations and presents the telescopic universal joint as a promising solution to improve the capabilities of rescue robots.
M. Kamezaki et al., "Design of four-arm four-crawler disaster response robot OCTOPUS," 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016, pp. 2840-2845, doi: 10.1109/ICRA.2016.7487447. This paper presents the OCTOPUS robot, which is equipped with four arms and four crawlers, providing it with high mobility and flexibility. The robot's arms are designed to have multiple degrees of freedom, enabling it to perform complex operations, such as opening doors and lifting heavy objects. The crawlers are designed to provide stability and traction, allowing the robot to move on uneven and slippery surfaces.
Park, S., Oh, Y. & Hong, D. Disaster response and recovery from the perspective of robotics. Int. J. Precis. Eng. Manuf. 18, 1475–1482 (2017). https://doi.org/10.1007/s12541-017-0175-4 --> This paper provides an overview of the role of robotic operations in disaster situations. The paper discusses the challenges faced by emergency responders and rescue teams in disaster-stricken areas, such as limited access to the affected areas, hazardous conditions, and limited resources.

Past projects

Universal Swarm Robotics Software Project
PRE2018 3 Group17
PRE2020_4_Group2

Problem Identification

We need to completely solve a problem!!
How money is distributed into SAR missions; making a cheap vine robot
Why use vine robot?
Problems with current rescue robots
Vine robots not implemented into real-life scenarios; no localization or path planning connected to it
Current autonomous level, what is preferred? (semi-autonomous for current situations)
A simulation can be used to find the best algorithm to find a safe path (path planning)
- Once the victim is localized, the simulation will 'start' for path planning
Research will be done on different sensors which can be to find victims (localization)

USE

Users

Within urban search and rescue operations, several users of the vine robot can be named.

First, the International Search and Rescue Advisory Group (INSARAG) determines the minimum international standards for urban search and rescue (USAR) teams (INSARAG – Preparedness Response, z.d.). This organization establishes a methodology for coordination in earthquake response. Therefore, this organization will have to weigh the pros and cons of using a vine robot in USAR. If INSARAG sees the added value of using robotics in search and rescue operations, it can promote the usage, and include it in the guidelines.

Second, governments will need to purchase all necessary equipment. For the Netherlands, Nationaal Instituut Publieke Veiligheid is the owner of all the equipment of the Dutch USAR team (Nederlands Instituut Publieke Veiligheid, 2023). This Institute will need to see the added value of the robot while taking into account the guidelines of INSARAG.

The third group of users consists of members of the USAR teams that will have to work with the vine robot on site. The vine robot will be used alongside other techniques that are already used right now. USAR teams are multidisciplinary and not all members of the team will come in contact with the robot (e.g., nurses or doctors). In order to properly use the vine robot, USAR members who execute the search and rescue operation will need training. For the Dutch USAR team, this training can be conducted by the Staff Officer Education, Training and Exercise (Het team - USAR.NL, z.d.). USAR members will need to be able to set up the vine robot, navigate it inside a collapsed building (if it is not fully autonomous), read data that the vine robot provides, and find survivors with the help of the vine robot. Furthermore, they will need to decide whether it is safe to follow the path of the vine robot to a survivor. Lastly, team members will need to retract the vine robot and reuse it if possible.

Difference in light/medium/heavy USAR teams

At last, the victims of the earthquake that the vine robot will be used for to localize. They will not have any control over the vine robot but will come into contact with it. It is therefore important that they will not be scared of the robot and will try to defend themselves from it.

In order to gather knowledge regarding the needs of these users, emails are sent out containing the following questions.

What type of sensors or technology do you use for localization?

How do you localize survivors?
- If there are methods that allow robots to go closer within rubble, are there specific things to keep in mind for localization?
What can your current equipment not do and what would you like them to improve on?
What is the main issue you have on current equipment?
What makes a rescue operation expensive?
What is the protocol for when you are unable to rescue a survivor? (e.g. assigning probabilities to survivors as resources are limited)

...

What do the users require?

Emergency services, victims and first responders require rescue robots to have certain capabilities and characteristics to make them effective in supporting disaster response efforts. Rescue robots need to be able to traverse difficult terrain, navigate obstacles, and travel long distances to reach victims and other areas of interest. Additionally, rescue robots should be able to provide a reliable and robust communication link between emergency responders and remote locations. This includes sustaining video and audio feeds, as well as other data such as maps, images, and sensor data. To hammer home on this last point, the rescue robot will need to have enough sensors to provide an accurate representation of its surroundings while communicating, since it might be important for the respondent to take possession over control from the robot. They must have sensors that can provide information about the environment and potential hazards, such as temperature, air quality, radiation levels, and gas leaks. This information can help responders make informed decisions about their actions and ensure their safety. Lastly, aside from being able to communicate with responders, these robots must have a certain degree of autonomy to be effective. They should be able to operate without human intervention for a certain period of time, navigate and map their environment, and avoid obstacles. Overall, rescue robots are required to be reliable, rugged, and capable of providing a high level of support in a disaster scenario.

Society

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Enterprise

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Specifications

The following specifications are made for what the vine robot is able to achieve. It should be noted that these specifications will only be depicted through literature research, where no prototype is being built.

Must:

Communicate back and forth
Move by command (e.g. muscle tube)
Use sensors for detection (e.g. visual, audio)
Be easy to transport
Be quick to setup

Should:

Supply water and air
Be relatively cheap and easy to manufacture

Could:

Communicate with other vine robots (e.g. swarm robots)
Autonomously find survivors (e.g. localization)
Inflate into safety structure
Retract back to its original path
Create a 3D model of the environment

Won't:

Actively get survivors out of situations (it only assists)
Supply heating or other health supplies other than water or air
Be infinitely long (it has a fixed length)
Be able to lift x kg
Be able to put out fires and melt in extreme heat

Research equipment + how to build (will be moved to 'Improvements' chapter at the end)

A simple vine robot can be created in a manner of minutes (Zepeda, 2022). The material list supplied with the 1-Minute Vine Robot tutorial also shows that it can be done quite cheaply. For a more robust robot, alternate materials can be chosen depending on the robot’s requirements (Coad et al., 2020).

This simple design does not yet suffice for the project’s goals, as the robot must be able to sense what is happening in front of it to find survivors. To achieve this, it is required to attach sensors to the tip of the vine robot. Several techniques have been developed to mount sensors and tools at the tip of a vine robot (Blumenschein et al., 2020). The technique that seems most suitable for this project uses rolling interlocks with a ball bearing mechanism. With this technique, the sensors are connected to an external frame, which is connected to the robot via ball bearings located inside the vine robot’s body (Zotomayor, 2021).

Scenario

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CAD Modelling

This CAD model shows a simple idea on how the tetrahedron safety structure would look like once fully inflated. The triangular shape was chosen due to it being very stiff under both tension and compression. In this case, it is ideal that the structure is stiff under compression, which the rubble would act on.

Storyboard

Storyboard of the Vine Robot in Action

This storyboard above depicts the use of the vine robot. Here, it can be seen that the vine robot maneuvers through the rubble of a collapsed building. With the strength of xxx plastic, it is able to withstand potential tears occurring from sharp edges of debris. With the ‘muscle’ tubes, the vine robot can change direction, depending its own interest, which in this case is to locate and find a survivor. Initially, the vine robot would move randomly within the rubble. Once a survivor is located, the ‘muscle’ tubes can be set into action, allowing the vine robot to navigate its own path. Once it has successfully reached the survivor, air pressure of the tubes would remove any debris off the survivor. Then, it inflates into a tetrahedron shape, allowing the survivor to crawl within in order to keep them safe from being crushed by other debris. The camera within this structure can visualize any injuries of the survivor and send this live data to the rescuers outside. Once a rescue plan has been made, the rescuers can start moving their way to the survivor and rescue them from under all the rubble.

Pathfinding and localization

Current Difficulties

Earthquakes are one of the most devastating natural disasters, causing widespread destruction and loss of life. One of the biggest challenges that emergency responders and aid organizations face in the aftermath of an earthquake is localizing victims. This task can be extremely difficult due to a variety of factors, including the scale of the disaster, the nature of the terrain, and the complexity of the affected infrastructure.

Firstly, the scale of the disaster is often overwhelming, making it difficult for rescue teams to quickly locate and reach those in need of assistance. Earthquakes can cause extensive damage to buildings, roads, and other infrastructure, which can make it challenging for rescue teams to navigate the affected areas. Additionally, earthquakes can cause landslides, debris flows, and other hazardous conditions that can further impede rescue efforts.

Secondly, the nature of the terrain can also make it difficult to localize victims after earthquakes. Many earthquakes occur in mountainous or hilly areas, which can be challenging for rescue teams to access. These areas may have steep slopes, narrow paths, and other obstacles that can make it difficult to reach victims. Additionally, earthquakes can cause landslides and rockfalls, which can further complicate rescue efforts.

Thirdly, the complexity of the affected infrastructure can also pose challenges for rescue teams. Earthquakes can damage roads, bridges, and other infrastructure, which can make it difficult for rescue teams to access affected areas. In addition, damage to communication networks can make it difficult for rescue teams to coordinate their efforts and share information about the location of victims.

Lastly, the timing of earthquakes can also complicate rescue efforts. Earthquakes can occur at any time, day or night, and may cause power outages, making it difficult for rescue teams to operate in the dark. Additionally, aftershocks can further damage infrastructure and create additional hazards, making it difficult for rescue teams to work safely.

In conclusion, localizing victims after earthquakes is a challenging task that requires extensive planning, coordination, and resources. The scale of the disaster, the nature of the terrain, the complexity of the affected infrastructure, and the timing of the earthquake can all pose significant challenges for rescue teams.

Localization for vine robots

Localization of surviors is a critical task in search and rescue operations in destroyed buildings. Vine robots can play an important role in this task by using their flexibility and agility to navigate through complex and unpredictable environment and locate survivors. Localization involves determining the position of the robot and the position of any survivors in the enviroment and can be achieved through a variety of techniques and strategies.

An approach to localization is to use a combination of sensors and algorithms to detect and track the location of survivors. This can include sensors that detect sound, heat or movement as as algorithms that use this data to determine the location of survivors in the environment.

Detecting of heat

Detecting of sound

Detecting movement

Pathfinding for vine robots

Pathfinding is the process of finding the shortest or most efficient path between two points in a given environment. For a vine robot, pathfinding is critical as it allows the robot to navigate throught the porous environment of destroyed buildings and reach its intended destination. Pathfinding algorithms are typically used to determine the best route for the robot to take based on factors such as obstacles, terrain and distance.

One approach is to use a combination of reactive and deliberative pathfinding strategies.Reactive pathfinding involves using sensors to detect obstacles in real-time and making rapid adjustments to the robot's path to avoid them. This can be especially useful in environments where the obstacles and terrain are constantly changing such as in a destroyed building. Deliberative pathfinding on the other hand involves planning paths ahead of time based on a map or model of the environment. While this approach can be useful in some cases, it may not be practical in a destroyed building where the environment is constantly changing.

Another approach is to use maching learning algorithms to train the robot to navigate through the enviroment based on real-world data.

Sensors and path planning

Colas et al. (2013) present a path planning that works for a 3D terrain. The system makes use of exteroceptive sensors, it uses a front-mounted rolling laser scanner that can take full three-dimensional (3D) scans of its surrounding. "This system is based on point cloud data and does not attempt to fully reconstruct the environment, but instead uses lazy tensor voting to assess traversability." Tensor voting means that it extracts geometrical primitives and saliency by voting of points So far, this system has been implemented for static environments, in dynamic environments it still has challenges. Which raises the question if our robot should be able to path plan in a dynamic environment and if this is useful for our robot.

Table 1: Sensor Research

When we look at the table provided we see use cases of how to detect people under debris, with the current technologies and how to continue research into them. Ferrara V. (2015), explains everything in the paper regarding the shortcomings and benefits of each solution. Giving us a good start to figure out what technologies we need to research. Provided below is some information about them, but each would need to be researched in depth. I think for the current project idea, one of the following would be enough to deepen in as the full research into one of these would already take too much time.

Constant false alarm rate (CFAR)

CFAR detection refers to a common form of adaptive algorithm used in radar systems to detect target returns against a background of noise, clutter and interference.

An important CFAR algorithm is the cell averaging (CA) CFAR, in which the mean background level is estimated by averaging the signal level in M neighboring range cells.

Self-injection-locked (SIL)

The SIL radar is operated at 433 MHz ISM band to achieve excellent penetration capability and coverage. Moreover, an additional phase shifter is utilized to eliminate the large frequency shift, which is caused by strong clutter signals and often causes the SIL mechanism to fail.

Ultra-wideband (UWB)

UWB has traditional applications in non-cooperative radar imaging. Most recent applications target sensor data collection, precise locating, and tracking. Ultra low-power radio-frequency identification (RFID) tag with precision localization is often the enabling technology for location-aware sensor applications. Impulse-Radio Ultra-Wideband (IR-UWB) is a promising technology to fulfill the usage requirements in indoor cluttered environment. This doesn't specifically mean that it will work well under interference or rubble for that matter, but it does show us some promising results.

Methods (sources will be added later)	Localizing Victims under Rubble	Localizing Victims Fast	Precision
Visual Recognition with Rescue Dogs	No	Yes	High
Life Signs Detector Using a Drone in Disaster Zones	No	Yes	High
Audio-Processing-Based Human Detection in Disaster Sites with Unmanned Aerial Vehicle	Maybe	No	Low
Methods for Autonomous Wristband Placement with a Search-and-Rescue Aerial Manipulator	No	No	Precise
Victim Localization Using Bluetooth Low-Energy Sensors	Yes	Yes	Precise only at the surface
Detection and Location of Victims Using WiFi FTM and UWB	Yes	Yes	Precise
(more sources will come)

Simulation

Goal

The goal of the simulation is to determine what algorithm is the best fit as our robot’s pathfinding algorithm and to prove the algorithm’s functionality. The algorithm can be split into two parts. First the vine robot has to find a sign of life by systematically searching through the debris. Then once the vine robot has picked up on such a sign of life, it must adjust its route to move towards the source of that sign of life in order to get the exact location of a survivor. The latter part of the algorithm is particularly of interest here, which is why we save this route. Aside, from relaying this information back, it’s also important for the stretch goal of having swarm robotics.

Specification

The simulation is made in a 2D environment using NetLogo, as the results can be mapped to a 3D environment and this saves on development cost compared to a 3D simulation. The vine robot is represented as a turtle in NetLogo. For algorithms involving swarm robotics, multiple turtles can be used.

The robot can move (diagonally) forwards, turn left, and turn right. It cannot move (diagonally) backwards. The robot cannot move onto patches it has visited before, because the vine robot would then hit itself. The robot can only see the patches towards which it can move. When involving swarm robotics we wouldn’t want them to cross each other either, thus by saving and relaying its path we can save on resources (vine robots don’t traverse the same path) and prevent them from crossing/crashing into each other.

The environment is randomly filled with large chunks of debris. These are represented by grey patches. The robot may not move onto these patches.

The environment also contains a sign of life, which is represented by a colored patch. When in an adjustable range of the sign of life, the robot can determine the direction of its source, but it cannot know the exact location until the target is reached. The algorithm used for getting to the target is of particular interest in this simulation. Once the robot has reached the target patch, the user is notified and the simulation is stopped.

Design choices

The simulation cannot represent the whole scenario. We had to make some design decisions where it may not be directly apparent as to why we chose them, thus some of our design choices will be explained further in detail here.

The first issue is clearly that NetLogo is a 2D environment, whereby we can map it to a 3D environment but this will clearly not be the full story. The vine robot itself can go underneath (and through) debris if there is an opening. That is the whole reason we chose the vine robot after all. While this does hold true, we must keep in mind what we’re trying to accomplish with the simulation. As we want to show a path finding algorithm for the robot to map out its environment while looking for any sign of life. The sensors should influence the route taken but the pathfinding algorithm should be robust enough to continue onwards when there is (or isn’t) any sensory information. Thus, missing the one dimension for our simulation will not influence the results that we would be looking for with the simulation.

In the simulation, the target patch cannot be one that indicates a large chunk of debris. Intuitively this would mean that the target patch is one with small, light debris which the vine robot can move through. However, we know that the target is stuck underneath rubble, as they would not need rescuing otherwise. As such, the target patch is assumed to be a location that contains a survivor who is stuck underneath rubble from which they cannot escape by themselves. Whether this is a single big piece of debris or a collection of smaller pieces of debris can be influential in getting the survivor out of the debris, but it is not important for finding them. Thus it is also not important for the simulation.

Weekly breakdowns

Name	Total	Breakdown week 1
Clinton Emok	3h	Meeting (1h), literature research (1h), user definition(1h)
Richard Farla	4h	Brainstorm session (1h), meeting (1h), literature research (1h), milestones (1h)
Yash Israni	3h	Meeting (1h), user requirements(1h), literature research (1h)
Tessa de Jong	4h	Brainstorm session (1h), meeting (1h), problem statement (1h), literature research (1h)
Kaj Scholer	4h	Brainstorm session (1h), meeting (1h), milestones (1h), literature research (1h)
Pepijn Tennebroek	4h	Brainstorm session (1h), meeting (1h), problem statement (1h), literature research (1h)

Name	Total	Breakdown week 2
Clinton Emok	6h	Meeting 1 (2h), Meeting 2 (2h), Meeting 3 (1h), Localization (1h)
Richard Farla	6h	Meeting 1 (2h), Meeting 2 (2h), Research equipment + how to build (2h)
Yash Israni	7h	Meeting 1 (2h), Meeting 2 (2h), Meeting 3 (1h), Sensors (2h)
Tessa de Jong	7h	Meeting 1 (2h), Meeting 2 (2h), Meeting 3 (1h), Literature research (2h)
Kaj Scholer	10.5	Meeting 1 (2h), Meeting 2 (2h), Meeting 3 (1h), CAD Modelling (2h), Storyboard (2.5h), Primary Reddit Research (1h)
Pepijn Tennebroek	7h	Meeting 1 (2h), Meeting 2 (2h), Meeting 3 (1h), Fix literature (1h), Research Pathplanning (2h)

Name	Total	Breakdown week 3
Clinton Emok	7h	Meeting 1 (2h), Meeting 2 (1h), Meeting 3 (1h), Writing paper (1h), Research(1h), State-of-the-art(1h)
Richard Farla	7h	Meeting 1 (2h), Simulation (3h), Meeting 2 (1h), Meeting 3 (1h)
Yash Israni		Simulation (1h), Meeting 2 (1h), Meeting 3 (1h)
Tessa de Jong		Meeting 1 (2h), Problem statement and Users (3h), Meeting 2 (1h), Meeting 3 (1h), Research (2h)
Kaj Scholer	8h	Meeting 1 (2h), Meeting 2 (1h), Meeting 3 (1h), Fixing Wiki Structure/Content (1h), State-of-the-art (1h), Localization + Sensors (2h)
Pepijn Tennebroek		Problem statement and Users (3h), Meeting 2 (1h), Fix literature (3h) Meeting 3 (1h)

References

AJLabs. (2023). Infographic: How big were the earthquakes in Turkey, Syria? Earthquakes News | Al Jazeera. https://www.aljazeera.com/news/2023/2/8/infographic-how-big-were-the-earthquakes-in-turkey-syria

Blumenschein, L. H., Coad M. M., Haggerty D. A., Okamura A. M., & Hawkes E. W. (2020). Design, Modeling, Control, and Application of Everting Vine Robots. https://doi.org/10.3389/frobt.2020.548266

Coad, M. M., Blumenschein, L. H., Cutler, S., Zepeda, J. A. R., Naclerio, N. D., El-Hussieny, H., Mehmood, U., Ryu, J., Hawkes, E. W., & Okamura, A. M. (2020). Vine Robots: Design, Teleoperation, and Deployment for Navigation and Exploration. https://arxiv.org/pdf/1903.00069.pdf

Urban Search and Rescue Team. (2023). Update zaterdagmiddag. USAR. https://www.usar.nl/

Zepeda, J. A. R. (2022). The 1-minute vine robot. Vine Robots. https://www.vinerobots.org/build-one/the-simple-vine-robot/

Zotomayor, C., (2021). This Vine Robot Is an Unstoppable Force With Tons of Applications. https://www.solidsmack.com/design/vine-robot/

F. Colas, S. Mahesh, F. Pomerleau, M. Liu and R. Siegwart, "3D path planning and execution for search and rescue ground robots," 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan, 2013, pp. 722-727, doi: 10.1109/IROS.2013.6696431. This paper presents a pathplanning system for a static 3D environment, with the use oflazy tensor voting.

Tai, Y.; Yu, T.-T. Using Smartphones to Locate Trapped Victims in Disasters. Sensors 2022, 22, 7502. https://doi.org/10.3390/ s22197502

Da Hu, Shuai Li, Junjie Chen, Vineet R. Kamat,Detecting, locating, and characterizing voids in disaster rubble for search and rescue, Advanced Engineering Informatics,

Volume 42,2019,100974,ISSN 1474-0346, https://doi.org/10.1016/j.aei.2019.100974

Appendix

User Study 1

Query:

I am currently doing a project about technology being used in search and rescue situations. As a group, we have come up with some questions. These questions are here to give us an idea on areas which can be improved, such as the problems with current equipment. If you have contact with other SAR organizations, we would be grateful if you can help us get into contact with them, so that we can further our analysis. Thank you all in advance!

What type of sensors/technology are currently used to localize a survivor?
What are the main issues with the current equipment or what do they lack in?
What makes a rescue operation expensive?
What are some protocols for when a survivor cannot be rescued?

Results: