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:

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

Existing rescue robots

The Current State and Future Outlook of Rescue Robotics

There exist various state-of-the-art rescue robots with promising future outlooks. However, achieving full autonomy in real-world rescue scenarios is presently challenging to implement. In fact, there is a marked inclination towards semi-autonomous behaviors, rather than complete manual control (Delmerico et al., 2019).

Robotically negotiating stairs

The technique for traversing stairs involves obtaining image data depicting a robot navigating through a stair-filled environment using either one or two legs. This method is highly comparable to crossing terrain that is cluttered with debris and fallen objects (Boston Dynamics, Inc., 2019).

Design of four-arm four-crawler disaster response robot OCTOPUS

The OCTOPUS robot, presented in this paper, boasts four arms and four crawlers, providing exceptional mobility and flexibility. Its arms are engineered with multiple degrees of freedom, enabling the robot to execute intricate tasks such as lifting heavy objects and opening doors. Furthermore, the crawlers are designed to offer stability and traction, which allow the robot to move seamlessly on irregular and slippery surfaces (Kamezaki et al., 2016).

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 (Nosirov et al., 2020).

Life Signs Detector Using a Drone in Disaster Zones

A new computer vision system has been developed to detect vital signs in hazardous zones using drones. The outcomes of the study indicate that the system can detect breathing patterns from an aerial platform with a high level of accuracy. The system effectively differentiates between humans and mannequins in daylight, with the aid of a human operator and a robust PC equipped with MATLAB (Al-Naji et al., 2019).

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

This study introduces a cheap robot designed for detecting humans in perilous rescue missions. The paper presents several system block diagrams and flowcharts to demonstrate the robot's operational capabilities. The robot incorporates a PIR sensor and IP camera to detect human presence through their infrared radiation. These sensors are readily available and cost-effective compared to other urban search and rescue robots (Uddin & Islam 2016).

Legged Robots That Balance

This study has significant implications for theories on human motor control and lays a fundamental groundwork for legged locomotion, which is one of the least explored areas of robotics. The study addresses the potential of constructing functional legged robots that can run and maintain balance (Raibert, 2000).

An Overview of Legged Robots

The present paper highlights the progress and the current state-of-the-art in the field of legged locomotion systems. The study examines various possibilities for mobile robots, including artificial legged locomotion systems, and discusses their benefits and drawbacks. It explores the advantages and limitations of such systems, providing insights into their potential for future advancements (Tenreiro Machado & Silva, 2006).

Designing, developing, and deploying systems to support human–robot teams in disaster response

The focus of this paper is on the creation, construction, and implementation of systems that aid in human-robot teams during disaster response. The paper has resulted in significant advancements in robot mapping, robot autonomy for operating in challenging terrain, collaborative planning, and human-robot interaction. The presentation of information considers the fact that these contexts can be stressful, with individuals working under varying levels of cognitive load (Kruijff et al., 2014).

Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities †

Snake robots have the potential to be equipped with sensors and tools to transport materials to areas that are hazardous or inaccessible to other robots and humans. Their flexible and slender design allows them to navigate through narrow and confined spaces, making them ideal for performing tasks in environments such as collapsed buildings or underground tunnels. By incorporating sensors and specialized equipment, snake robots can operate in a variety of hazardous environments, including those with high levels of radiation or toxic chemicals, without putting human workers at risk. They "expanded the description for increasing the level of autonomy within three main robot technology areas: guidance, navigation, and control" (Sanfillipo et al., 2017).

Robotic Urban Search and Rescue: A Survey from the Control Perspective

The current paper presents an extensive review of advancements in robotic control for urban search and rescue (USAR) settings, which is an exciting and challenging field of research. The paper covers the development of low-level controllers to facilitate rescue robot autonomy, task sharing between the operator and robot for multiple tasks, and high-level control schemes designed for multi-robot rescue teams. These innovations aim to improve the functionality, reliability, and effectiveness of rescue robots in disaster response scenarios, which can help save lives and minimize damage (Liu & Nejat, 2013).

Robots Gear Up for Disaster Response

Although brilliant robotic technology exists, there is a need to integrate it into complete, robust systems. Furthermore, there is a need to develop sensors and other components that are smaller, stronger, and more affordable (Anthes 2010).

Active scope camera for urban search and rescue

The focus of this paper is the design and implementation of an Active Scope Camera (ASC) for urban search and rescue (USAR) operations. The ASC is a small, lightweight device that can be deployed to explore confined spaces and provide visual information to rescuers (Hatazaki et al., 2007).

The design of telescopic universal joint for earthquake rescue robot

This paper describes a transmission system that includes a telescopic universal joint, which is used in a snake-like search and rescue robot. The paper emphasizes the importance of designing flexible and adaptable robotic systems that can be used effectively in rescue operations. The telescopic universal joint is highlighted as a promising solution to enhance the capabilities of rescue robots. The paper provides details on the design and construction of the joint, which allows the robot to navigate through narrow spaces and tight corners while maintaining its structural integrity. By improving the flexibility and mobility of rescue robots, such as with the telescopic universal joint, search and rescue operations can become more effective and efficient, potentially saving lives in critical situations (Zhao et al., 2016).

Multimodality robotic systems: Integrated combined legged-aerial mobility for subterranean search-and-rescue

This article discusses a Boston Dynamics Spot robot that is enhanced with a UAV carrier platform, and an autonomy sensor payload (Lindqvist et al., 2022). The paper demonstrates how to integrate hardware and software with each other and with the architecture of the robot.

The EU-ICARUS project: Developing assistive robotic tools for search and rescue operations

This paper describes the ICARUS tools (De Cubber et al., 2013). One of these tools is a small lightweight camera system that should be able to detect human survivors. According to this article, an infrared sensor with high sensitivity in the mid-IR wavelength range would be the most adequate detection instrument.

This paper mentions that technological tools are no good for USAR teams if they do not know how to make use of them. Therefore, training and support infrastructure is required. In order to do this, e-training and trainers-simulators can be used.

Detecting Earthquake Victims Through Walls

This article is about a new radar system that is able to detect human breathing and movement through walls (Hampson, 2022). The system uses Doppler radar to measure small changes in electromagnetic waves caused by body movements and breathing. This could be helpful in USAR operations. However, the article also mentions concerns about privacy and researchers emphasize the need for ethical considerations.

Land-Mobile Robots for Rescue and Search: A Technological and Systematic Review

This article discusses sensors that are used to obtain data on the robot’s environment based on 26 papers on rescue and search robots (Huamanchahua et al., 2022). For remote teleoperation cameras are most often used (in 96% of the cases). For identifying victims, 3D mapping and/or image processing is most often used (96%). In around 50% of the papers, microphones are used for human detection. Furthermore, CO2 sensors are used in 73% of the papers. Lastly, in 30% of the cases, temperature sensors are used to measure the victim’s body temperature.

Review Paper on Search and Rescue Robot for Victims of Earthquake and Natural Calamities

This article reviews search and rescue robots designed to locate and assist survivors of natural calamities (Bangalkar & Kharad, 2015). It concludes that these robots have the potential to save lives after natural disasters, and it mentions the need for continued research and development in this area.

Rescue robots in action

Disaster Robotics

This book offers a comprehensive overview of rescue robotics within the broader context of emergency informatics. It provides a chronological summary of the documented deployments of robots in response to disasters and analyzes them formally. The book serves as a definitive guide to the theory and practice of previous disaster robotics (Murphy, 2017).

Application of robot technologies to the disaster sites

For the first time during the Great East Japan Earthquake disaster, Japanese rescue robots were utilized in actual disaster sites. Their tele-operation function and ability to move on debris were essential due to the radioactivity and debris present (Osumi, 2014).

Utilization of Robot Systems in Disaster Sites of the Great Eastern Japan Earthquake

After deploying robots in recovery operations, three key lessons were learned. Firstly, rescue robots are valuable not only for response but also for economic and victim recovery. Secondly, disaster robots need to be optimized to suit the specific missions and stakeholder requirements. Lastly, human-robot interaction continues to pose a challenge (Matsuno et al., 2014).

Emergency response by robots to Fukushima-Daiichi accident: summary and lessons learned

Numerous lessons were learned from the emergency response of robots to the accident, with a focus on the organization and operation scheme as well as systemization (Kawatsuma et al., 2013).

Use of active scope camera in the Kumamoto Earthquake to investigate collapsed houses

The paper discusses the use of the Active Scope Camera (ASC) in the aftermath of the 2016 Kumamoto earthquake in Japan. It explains how the ASC was instrumental in providing crucial information to rescue teams, resulting in the successful rescue of multiple trapped occupants. The paper emphasizes the significance of utilizing advanced imaging technologies like the ASC in urban search and rescue operations, as they can improve the effectiveness and safety of rescue workers (Ambe et al., 2016)

Disaster response and recovery from the perspective of robotics

This paper presents a summary of the use of robotic operations in disaster scenarios. It examines the difficulties encountered by emergency responders and rescue teams in disaster-affected regions, including restricted access to the affected areas, dangerous conditions, and scarce resources (Park et al., 2017).

Drone-assisted disaster management: Finding victims via infrared camera and lidar sensor fusion

This article mentions that the use of drones has proven to be an efficient method to localize survivors in hard-to-reach areas (e.g., collapsed structures) (Lee et al., 2016). The paper presents a comprehensive framework for drone hardware that makes it possible to explore GPS-denied environments. Furthermore, the hokuyo lidar is used for global mapping, and the Intel RealSense for local mapping. The outcomes show that the combination of these sensors can assist USAR operations to find victims of natural disasters.

Boston Dynamics’ Spot Is Helping Chernobyl Move Towards Safe Decommissioning

This article presents the Boston Dynamics’ Spot robot. It discusses that the robot can be used to inspect and monitor the structural integrity of buildings (Ackerman, 2020). The robot has potential as it can perform dangerous tasks in hazardous environments which reduces the risk for human workers.

Rescue Robots for the Urban Earthquake Environment

The utilization of robots in USAR operations can decrease response time, enhance the effectiveness of rescue operations, and ensure the safety of USAR personnel (Li et al., 2022). However, when testing the robot in Italy, the robot operator experienced cognitive overload. The data provided by the robot was not intuitive, so much information still had to be managed by people. Consequently, rescue personnel with limited training were unable to effectively control the robot on site.

Earthquake sites

Rescue robotics: DDT project on robots and systems for urban search and rescue

Tremors caused by an earthquake destroy buildings, can generate tsunamis, and cause fires, landslides, etc. (Tadokoro, 2009). Due to this, inhabitants can be buried alive, burnt to death, or drowned. Immediate USAR is important as the survival rate decreases as time passes. Especially, the first 72 hours are important and called the golden 72 hours. “Many first responders state that they can rescue if the victim’s position is known. Often, search is beyond human ability” (Tadokoro, 2009, p. 11). This book names equipment used in USAR. Among others, these are an infrared camera to detect human survivors, microwave radar to detect heartbeats, and a fiber scope which is a bending camera.

USAR experiences

Urban Search and Rescue Team. Update zaterdagmiddag

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 survivors for several days.

Previous projects

PRE2015 2 Groep1 - Universal Swarm Robotics Software Project

Swarm robotics used for helping people in the debris after an earthquake. The robots communicate with each other to help each other in order to remove rubble.

PRE2018 3 Group17

This group presented drone robotics in order to seek for survivors. The drones were controlled via radio control on a 900 MHz frequency.

PRE2020_4_Group2

This project researched how a swarm of RoboBees (flying microbots) could be used in USAR operations. The main concern of this project was to identify the location of a gas leak and to communicate that information to the USAR team. They looked into infrared technology, wireless LAN and bluetooth for communication.

Problem Identification

The problem that will be addressed throughout this paper is the development of a cost-effective vine robot to be used in urban search and rescue (USAR) missions. These missions are known to be extremely critical, which require precise technology to navigate and locate survivors through complex terrain. However, current rescue robots have multiple limitations which make it difficult for them to be used successfully. As a result, this paper will explore the vine robot as an alternative solution.

To this day, vine robots have not been implemented into critical USAR missions, since they do not have any navigation or localization abilities. Therefore, research needs to be conducted to solve this problem and allow vine robots to be used in real-life rescue missions. The most suitable sensors will need to be identified for localization, as well as the preferred navigation strategy. On top of this, the level of autonomy will need to be analyzed for the vine robots application.

Overall, current rescue robots have have limitations such as mobility issues, limited sensing and limited autonomy. As a result, this paper will explore these problems and come up with a viable solution for the vine robot to be used in real-life USAR applications.

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.

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.  

Users' needs

In order to gather knowledge regarding the needs of these users, emails are sent out to several USAR teams, INSARAG, and Nationaal Instituut Publieke Veiligheid, containing the following questions:

1. What type of sensors or technology do you use for localization?
2. 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?
3. What can your current equipment not do and what would you like them to improve on?
4. What is the main issue you have on current equipment?
5. What makes a rescue operation expensive?
6. What is the protocol for when you are unable to rescue a survivor? (e.g. assigning probabilities to survivors as resources are limited)

Questions for Nationaal Instituut Publieke Veiligheid:

1. How is it determined what material is bought for USAR operations?
2. How do you feel about using robotics in USAR operations?
3. What makes a rescue operation expensive?

Furthermore, similar questions were posted on Reddit, which can be found in the Appendix with the answers that we got. For the first query on reddit we got some responses, which can also be found in the appendix. The answers keep coming back to the main problem right now with the technology, which is that it is very expensive. The equipment that they use is expensive as is the training that the people have to have had for using their equipment. The second time we posted on reddit we got one answer of an USAR search specialist. What this USAR search specialist says there is that they do not really use technology right now because dogs are much more effective for finding an area that has an person in it. They use technology when trying to look for the exact spot that the person is in, but this technology has many disadvantages. Since they can not can reach deep into the debris.

Society

Society will benefit from vine robots as it will help USAR operations to localize victims and find a path within rubble to a victim. This will influence the time needed to search for survivors after earthquakes. This is important as the chances of surviving decrease with each passing day. Thus the usage of vine robots will influence the number of people that can be saved.

Enterprise

If the vine robot will be available for sale, the company behind it will have several interests. First, it will want to create a robot that can make a difference. The robot should help USAR operations with localizing survivors in the rubble. Second, the company will want to either make a profit or make enough money to break even. It will need money to invest back in the product to further improve the robot. For the company, it is important to take into account the guidelines of INSARAG as this institute will promote the usage of rescue robots in their global network.

Specifications

Before identifying the solutions for navigation and localization, a clear list of specifications for the vine robot is given.

Must:

• The vine robot must communicate from the tip of the vine, back to its starting location (the pump). This would allow the rescuers to communicate with the survivor by providing live feedback.
• For its application, the vine robot must be semi-autonomous. A human operator must move the vine robot by command, as well as the robot maneuvering itself when xxx???
• Sensors must be used for localizing the survivor. The exact sensors will be explored in the next chapter.
• Since the vine robot is to be used in critical rescue missions, it must be easy to transport and quick to setup. This would make it easier to increase the number of vine robots used in USAR missions, which increases the overall success rate in localizing survivors

Should:

• The vine robot should supply water and air once they have localized the survivor and navigated towards them. This would make sure that the survivor can stay conscious with essential needs before the rescuers come to evacuated them.
• It should be relatively cheap and easy to manufacture, allowing them to be mass produced.

Could:

• Once the autonomy level is sufficient enough, the vine robots could communicate with other vine robots. This swarm robotics would allow the vine robots to cover a larger area efficiently.
• The vine robot could retract back to its original path. This would allow the rescuers to reuse the vine robot for other rescue missions instead of wasting the money and technology.
• Inflate into safety structure, allowing the survivor to be protected from within, in case more rubble starts to fall on top of them.
• (Create a 3D model of the environment)

Won't:

• The vine robot is a technology that will only assist rescuers during USAR missions. It won't be able to actively get survivors out of situations, as it will not have the capabilities to evacuate them.
• 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

Now that the specifications have been determined, the constraints of the robot can be established. This mainly focuses on the design of the robot, such as the material and size.

Constraints:

• Size:
• Material:
• Weight:
• Cost: The cost of the vine robot should be reasonable and affordable for rescue teams to deploy. For the base of the robot this will be about €700,-, including one vine robot body, aditional bodies are €40,- per body (Vine robots, z.d.). The sensor need to be then included, based on which one is best after research.
• Load Capacity: The vine robot makes sure that the pressure within the body is 3,5 psi (Vine robots, z.d.). This means that the pressure is 0.246 kg/cm and thus depending on the length of the body at that time how much it can hold.
• Mobility: The vine robot should be able to navigate through tight spaces and climb up surfaces with ease. It can go trough gaps as small as 4.5 centimeter with a diameter of 7 centimeter (Coad et al., 2020).
• Growth speed: The vine robot right now can grow at a maximum speed of 10 cm/s (Coad et al., 2020).
• etc (more to be added)

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 survivors 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 environment 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. What current technology has these capabilities?

Detecting of heat

Vine robots can be equipped with a range of sensors that enable them to detect heat in their surroundings. Infrared cameras and thermal imaging systems are among the most commonly used sensors for detecting heat in robots.

Infrared cameras work by detecting infrared radiation emitted by objects and converting it into visual representations that can be interpreted by the robot's control systems.

Add diagram for infrared 

Thermal imaging systems use a more advanced technology that can detect temperature changes with higher precision, which can enable vine robots to identify potential sources of heat and determine the location and movement of individuals in a given environment

Add diagram for thermal imaging

Other types of sensors that could be used in vine robots for detecting heat also include contact sensors or gas sensors.

Contact sensors can be used to detect heat sources that come into direct contact with the robot's sensors. For example, if a vine robot comes into contact with a hot object such as a stove or a piece of machinery, the heat from the object can be detected by the contact sensors.

Gas sensors can be used to detect the presence of combustible gases such as methane or propane which can be an indicator of a potential fire or explosion

Detecting of sound

Detecting sound is another critical capability for vine robots especially in search and rescue operations. Vine robots can be equipped with a range of sensors that enable them to detect and interpret sound waves in their surroundings. A common type sensor used to detect sound is a microphone. Microphones can be used to capture sound waves in the environment and convert them into electrical signal that can be interpreted by the robot's control systems or be communicated back to a human operator for analysis

Ultrasonic sensors

Vine robots can also be equipped with ultrasonic sensors which enable them to detect sound waves that are beyond the range of human hearing. Ultrasonic sensors work by emitting high-frequency sound waves that bounce off objects in the environment and return to the sensor, producing an electrical signal that be interpreted by the robot's control systems.

Vibration sensors

In addition to ultrasonic sensors, vine robots can be equipped with vibration sensors, which can detect sound waves that are not audible to the human ear. Vibration sensors work by detecting the tiny vibrations in solid objects caused by sound waves passing through them. These vibrations are converted into electrical signals that can be interpreted by the robot's control systems.

Detecting movement

Detecting movement is another critical capability for vine robots, especially in search and rescue operations. Vine robots can be equipped with a range of sensors that enable them to detect and interpret movement in their surroundings.

Cameras

One common type of sensor used in vine robots for detecting movement is a camera. Cameras can be used to capture visual data from the environment and interpret it using computer vision algorithms to detect movement.

Motion sensors

Another type of sensor used in vine robots for detecting movement is a motion sensors.

Motion sensors or motion detectors are electronic devices that are designed to detect movement in their surrounding environment. They work by measuring changes in the level of infrared radiation, sound waves or vibrations caused by movement.

There are 4 types of motion sensors being used in the industry:

1. Passive infrared (PIR) sensors: These sensors detect changes in the level of infrared radiation (heat) in their field of view caused by moving objects.
2. Ultrasonic sensors: These sensors emit high-frequency sound waves and measure the time it takes for the waves to bounce back after an object. If an object moves in front of the sensors, it will cause a change in the time it takes for the sound waves to bounce back, which triggers an response.
3. Microwave sensors: Similar to ultrasonic sensors. But these sensors emit electromagnetic waves instead.
4. Vibration sensors: These sensors measure changes in acceleration caused by movement.

Add diagrams for detection types.

Sensors in Localization

The sensor types above have already explained the basics of detecting a human, where now an evaluation will be made, including other sensors.

Sources to come....

Sensor Type	Range	Resolution	Accuracy	Durability	Ease of Use	Cost	Ranking
Thermal Imaging	Long	High	High	High	Medium	High	1
Gas Detector	Medium	High	High	High	High	Medium	2
Chemical Sensor	Short	Medium	High	Medium	High	Low	3
Light Detection and Ranging (LiDaR)	Short	High	High	Medium	High	Low	4
Global Positioning System (GPS)							5
Magnetometer							6
Infrared Sensor							7

Ranking Criteria:

• Range: Maximum distance the sensor can detect an object
• Resolution: The smallest object the sensor can detect
• Accuracy: The precision of the measurements
• Durability: The ability of the sensor to withstand severe conditions (e.g. heat, humidity, impact)
• Ease of Use: How easy it is to operate the sensor
• Cost: The cost of the sensor

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 matching learning algorithms to train the robot to navigate through the environment 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

Our group has decided to construct a simulation for the localization capabilities of the Vine Robot. For a Vine Robot to accurately determine the location of a target, the robot must be able to get in close proximity to that target. As such, the robot’s localization algorithm must include pathfinding capabilities. The simulation will be used to test out how a customly developed localization algorithm picks up stimuli from the environment and reacts to these stimuli to then try and locate the survivor from whom these stimuli originate. For the simulation to succeed, the robot is required to reach the survivor’s location in at least 75% of the randomly generated scenarios.

The complexity of creating such a vine robot and its testing environment, due to the sheer amount of different possible scenarios and variables involved in finding survivors within debris, is currently outside of the scope of this course. However, we believe that the noisy environment and the robot can be simulated to retain their essential properties. The simulated environment will be generated using clusters of debris, with random noise representing interference, and intermittent stimuli that indicate the presence of a survivor. The random noise and intermittent stimuli are critical in simulating the robot’s sensors, since the data received from the sensors are limitedly reliable when going through debris.

Furthermore, our assumption for manoeuvrability of the Vine Robot within the simulation is that it has reached a level of precision similar to that of a snake. Which is something the current state of the art Vine Robots aren’t, but we expect this to be the standard level of manoeuvrability in the future.

Specification

The simulation is made using NetLogo 3D. This software has been chosen for its simplicity in representing the environment using patches and turtles.

The vine robot is represented as a turtle. For algorithms involving swarm robotics, multiple turtles can be used. The robot can move (diagonally) forwards and to its (diagonal) sides.. 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. To simulate the debris from collapsed buildings more closely, the debris patches are clustered together.

The environment also contains a survivor, which is represented by a stationary turtle. When within an adjustable range of the survivor, the robot can pick up on a sign of life. Once this happens, the robot can determine the direction of the 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 survivor, 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.

In the simulation, the survivor cannot be inside a patch that indicates a large chunk of debris. Intuitively this would mean that the survivor is stuck in 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, it is assumed that the weight of all the rubble underneath which the survivor is trapped prevents them from moving into another patch. The robot, however, is able to move between patches of small, light debris due to its lesser size. Whether the weight is caused by 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	6h	Simulation (1h), Meeting 2 (1h), Meeting 3 (1h), Researching papers (3h)
Tessa de Jong	9h	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	8h	Problem statement and Users (3h), Meeting 2 (1h), Fix literature (3h) Meeting 3 (1h)

Name	Total	Breakdown week 4
Clinton Emok		Meeting 1 (2h), Localization/Sensors (3h), Meeting 2 (30min), Meeting 3 (15min)
Richard Farla	7.75h	Meeting 1 (2h), Simulation (5h), Meeting 2 (30min), Meeting 3 (15min)
Yash Israni	5.75h	Meeting 1 (2h), Simulation (3h), Meeting 2 (30min), Meeting 3 (15min)
Tessa de Jong		Meeting 1 (2h), State-of-the-art (3h), USE (3h), Meeting 2 (30min),
Kaj Scholer		Meeting 1 (2h), Meeting 2 (30min), Problem statement (1.5h), Specifications (2h), Meeting 3 (15min)
Pepijn Tennebroek	9.75h	Meeting 1 (2h), State-of-the-art (4h), USE (3h), Meeting 2 (30min), Meeting 3 (15min)

Name	Total	Breakdown week 5
Clinton Emok		Meeting 2 (2h), Meeting 2.5 (0.5h)
Richard Farla		Meeting 1 (1h 30min), Meeting 1.5 (1h), Simulation brainstorm (2h), Meeting 2 (2h), Process simulation feedback (30min), Meeting 2.5 (0.5h)
Yash Israni		Meeting 1.5 (1h), Meeting 2 (2h), Meeting 2.5 (0.5h), Simulation (3h)
Tessa de Jong		Meeting 1 (1h 30min), Reddit posts (30 min), Meeting 2 (1h)
Kaj Scholer		Meeting 1 (1h 30min), Meeting 2 (1h 30min), Sensor research (2h),
Pepijn Tennebroek		Meeting 1 (1h 30min), Meeting 2 (2h)

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

Park, S., Oh, Y., & Hong, D. (2017). Disaster response and recovery from the perspective of robotics. International Journal of Precision Engineering and Manufacturing, 18(10), 1475–1482. https://doi.org/10.1007/s12541-017-0175-4

Raibert, M. H. (2000). Legged Robots That Balance. MIT Press

Tenreiro Machado, J. A., & Silva, M. F. (2006). An Overview of Legged Robots

Murphy, R. R. (2017). Disaster Robotics. Amsterdam University Press

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

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

Boston Dynamics, Inc. (2019). Robotically negotiating stairs (Patent Nr. 11,548,151). Justia. https://patents.justia.com/patent/11548151

Nosirov, K. K., Shakhobiddinov, A. S., Arabboev, M., Begmatov, S., and Togaev, O.T. (2020) "Specially Designed Multi-Functional Search And Rescue Robot," Bulletin of TUIT: Managementand Communication Technologies: Vol. 2 , Article 1. https://doi.org/10.51348/tuitmct211

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

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

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

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

Anthes, Gary. Robots Gear Up for Disaster Response. Communications of the ACM (2010): 15, 16. Web. 10 Oct. 2012

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

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_

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

Hatazaki, K., Konyo, M., Isaki, K., Tadokoro, S., and Takemura, F. (2007)  Active scope camera for urban search and rescue IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA, 2007, pp. 2596-2602, doi: 10.1109/IROS.2007.4399386

Ambe, Y., Yamamoto, T., Kojima, S., Takane, E., Tadakuma, K., Konyo, M., & Tadokoro, S. (2016). Use of active scope camera in the Kumamoto Earthquake to investigate collapsed houses. International Symposium on Safety, Security, and Rescue Robotics. https://doi.org/10.1109/ssrr.2016.7784272

Zhao, L., Sun, G., Li, W., & Zhang, H. (2016). The design of telescopic universal joint for earthquake rescue robot. 2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS). https://doi.org/10.1109/acirs.2016.7556189

Kamezaki, M., Ishii, H., Ishida, T., Seki, M., Ichiryu, K., Kobayashi, Y., Hashimoto, K., Sugano, S., Takanishi, A., Fujie, M. G., Hashimoto, S., & Yamakawa, H. (2016). Design of four-arm four-crawler disaster response robot OCTOPUS. International Conference on Robotics and Automation. https://doi.org/10.1109/icra.2016.7487447

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.

Ackerman, E. (2023i). Boston Dynamics’ Spot Is Helping Chernobyl Move Towards Safe Decommissioning. IEEE Spectrum. https://spectrum.ieee.org/boston-dynamics-spot-chernobyl

Lee, S., Har, D., & Kum, D. (2016). Drone-Assisted Disaster Management: Finding Victims via Infrared Camera and Lidar Sensor Fusion. 2016 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE). https://doi.org/10.1109/apwc-on-cse.2016.025

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

Li, F., Hou, S., Bu, C., & Qu, B. (2022). Rescue Robots for the Urban Earthquake Environment. Disaster Medicine and Public Health Preparedness, 17. https://doi.org/10.1017/dmp.2022.98

Tadokoro, S. (Ed.). (2009). Rescue robotics: DDT project on robots and systems for urban search and rescue. Springer Science & Business Media.

Hampson, M. (2022). Detecting Earthquake Victims Through Walls. IEEE Spectrum. https://spectrum.ieee.org/dopppler-radar-detects-breath

Huamanchahua, D., Aubert, K., Rivas, M., Guerrero, E. L., Kodaka, L., & Guevara, D. C. (2022). Land-Mobile Robots for Rescue and Search: A Technological and Systematic Review. 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS). https://doi.org/10.1109/iemtronics55184.2022.9795829

Bangalkar, Y. V., & Kharad, S. M. (2015). Review Paper on Search and Rescue Robot for Victims of Earthquake and Natural Calamities. International Journal on Recent and Innovation Trends in Computing and Communication, 3(4), 2037-2040.

Blines. (2023). Project USAR. Reddit. https://www.reddit.com/r/Urbansearchandrescue/comments/11lvoms/project_usar/

ManOfDiscovery. (2023).Technology in SAR. Reddit. https://www.reddit.com/r/searchandrescue/comments/11bw8qh/technology_in_sar/

WinnerNot_aloser. (2023).Technology in SAR. Reddit. https://www.reddit.com/r/searchandrescue/comments/11bw8qh/technology_in_sar/

Zook_Jo. (2023).Technology in SAR. Reddit. https://www.reddit.com/r/searchandrescue/comments/11bw8qh/technology_in_sar/

Vine robots. (z.d.). Vine Robot Base Bill of Materials [Dataset]. https://docs.google.com/document/d/116dmSj30YTTIdREIyxc65BnzAhu0tS0XKFy5Wbvn4V4/edit

Vine robots. (z.d.). Vine Robot Body Bill of Materials [Dataset]. https://docs.google.com/document/d/1OhQgyFUZ33Q_gsACnn7N8mZ0xsyPPV8LrQdCgpysmGw/edit

Vine robots. (z.d.). Vine Robot Base Building Instructions [Presentationslides; Google slides]. https://docs.google.com/presentation/d/1EgZlK4-h8C8dYxRFinapzcK7766c7cjgJA-kvjLgQuY/edit#slide=id.p

Localization/Sensors

Agarwal, T. (2019, July 25). Vibration Sensor: Working, Types and Applications. ElProCus - Electronic Projects for Engineering Students. https://www.elprocus.com/vibration-sensor-working-and-applications/#:~:text=The%20vibration%20sensor%20is%20also,changing%20to%20an%20electrical%20charge

Agarwal, T. (2022, May 23). Different Types of Motion Sensors And How They Work. ElProCus - Electronic Projects for Engineering Students. https://www.elprocus.com/working-of-different-types-of-motion-sensors/

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:

"Currently GPS devices are the most adopted tech used to localize injured parties. There are also a number of devices used by backcountry skiers including chips sewn into clothing that can be read when nearby if they’re buried in an avalanche. I’ve also heard of devices used that are similar to what structure fire uses if they don’t move for a given period of time, a loud alarm signal will sound.

Excluding training, what makes an operation expensive is the man-hours involved. And if there are air assets involved, cost can rise exponentially.

The primary issues with current equipment is often funding based. The few SAR operations that do receive routine funding are constantly having to pinch pennies.

Assuming precise location is known, protocols for when a survivor or body cannot be retrieved are incredibly situational and would primarily revolve around rescuer safety. Usually this takes the form of delayed rescue/recovery. It’s not as if people just throw in the towel." (ManOfDiscovery, 2023).

"If your talking wilderness interface SAR I’m a newbie so I can’t say much. But in terms of Urban SAR you’re talking well over a million dollars worth of equipment and training usually though grants will help with that.

With Urban Search there’s all different kinds of technology. Being a dept that gets UASI grants we have sonar type technology that can pinpoint sound coming from within a collapse. We’ll get choppers on scene providing light. We have thermal imagers and drones that also provide thermal coverage. Arc GIS for on scene operational coordination and to map the scene. Multi gas meters and radiation detectors. HazMat teams on standby. Technical rescue teams with different specialties. High angle rescue in a building collapse. That equipment isn’t cheap. 3 grand worth of individual kit for each tech team member plus I don’t know 50 thousand dollars worth of equipment. Trench rescue equipment maybe another 50 thousand. Collapse rescue teams have another 300 thousand dollars worth of equipment I’d assume. Wood for shoring, we have a truck that just has wood on it, so 200 grand for that. SCBA has to be on for confined spaces each of our ensembles is 5 grand and I’d guess we have have 60 ensembles department wide. Probably more. An air truck costs 150 grand maybe more. Training is extremely expensive full scale event can cost 50 thousand dollars high end. What makes these situation expensive typically is shear size of it and the amount of equipment and personnel required. If it’s a long enough scene we’ll have a fuel truck come out and refuel our rigs. In terms of victims not being able to be rescued. We try and rescue everyone (everyone gets recovered), the people who are easiest to rescue get rescued first but while that’s going on there’s a command post discussing how to rescue those who are harder to access. For urban sar useful technology would be I don’t know some kind of radiological imaging technology that could be deployed rapidly and get us a view of everything under a collapse. And have AI find us and map us to victims." (WinnerNot_aloser, 2023).

"If a victim has a cell phone tracking them is fairly easy. Multiple programs like what3words and sartopo allow search teams to locate a victim with a phone. Sattalites were massive for uptodate areial images.

Drones have massive applications in SAR.

I believe there is very little issue in current equipment other than cost, some equipment is very expensive for what it is.

Rescue OPS are expensive because it often requires extensive manpower, and the afformentioned equipment.

Being unable to rescue a victim isn't in our vocabulary, at worst we have to triage and put a victim on the backburner so to speak for a higher risk vicitm to be rescued. But until a rescue becomes a recovery, if there's a will there is a way.

Please forgive any spelling mistakes, working of a phone atm." (Zook_Jo, 2023).

User Study 2

Query:

Hi, I am currently doing a project on the usage of robotics in urban search and rescue, specifically after earthquakes. In order to understand the needs of the users, we have some questions:

• How do you localize survivors in rubble at the moment?
• What type of technology do you use at the moment?
• What type of sensors do those technologies use?
• If there are any, what issues do you have with your current methods for localization?
• Are there other things that you would like your equipment to improve on?
• How do you feel about the usage of robotics in USAR?
• What do we need to take into account when designing a robot used in USAR?

Results:

"USAR Search Spec here. In a collapse we are basically in 2 types of search. K9 and technical. We use live find dogs to search the areas to locate possible victims..... technology is nowhere near sophisticated enough to do what a dog does so robots are out. So lets move on to technical shall we.

In technical we have 2 categories. Looking and listening. For acoustic searches we use an array of sensors placed around the pile. We will call outbfor them to make some noise or bang on something then listen in. We can isolate and listen to each individual sensor. From there we will move the array and repeat the process. We can then start to triangulate based on intensity where we think a victim may be located. There are a couple companies that make these but the Del Sar has been the gold standard for a while.

So the other method is using cameras. Simplest terms is an articulating camera on an extendable boom that we can stick into void spaces to search. Usually DelSars and dogs will give us an idea of where to start. The newest versions of these cameras (Zistos search cam) has multiple heads we can put on with IR or 40x zoom and that helps a lot. There is also a newish camera that has a 360 camera on it (firstlook 360). That doesnt articulate manually. But we can stick it in a void and on the tablet look around.

As far as technologies we dont have thatbrobotics may solve..... remember in Prometheus. The Pups. They scanned the areas and were able to create a 3D rendering of the tunnels. Something like that would be amazing. It would help us look for void spaces or recreate the building based on what we see.

Another limitation we have with the cameras is the boom and the boom length. We can only go in about 12' and thats if we get straight back. There are fiber optic cameras but they dont have a way to control them at the head. So a tethered walking robot with legs and a camera would allow us to go much deeper without having to get the rescue guys out to start breaking concrete." (Blines, 2023).