PRE2022 3 Group2: Difference between revisions

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In active use the robot has to guide rescuers to possible locations of survivors in the environment. This scenario can be described in PEAS as:
In active use the robot has to guide rescuers to possible locations of survivors in the environment. This scenario can be described in PEAS as:


*Performance Measure:
*Performance Measure: The performance measure for the vine robot in the simulation would be the number of survivors found within a given time frame.
*Environment:
*Environment: The enviroment for the vine robot in the simulation would be a disaster zone with multiple clusters of debris. The debris can be of varying sizes and shapes and may obstruct the robot's path.
*Actuators
*Actuators: The actuators for the vine robot in the simulation would be the various robotic mechanisms that enable the robot to move and interact with its enviroment.
*Sensors:
*Sensors: The sensors for the vine robot in the simulation would include a set of cameras and microphones to capture diffferent stimuli. Additionally, the robot would also have sensors to detect obstacles in its path.




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|Clinton Emok
|Clinton Emok
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|Meeting 1 (2h)
|Meeting 1 (2h), PEAS (2h), Simulation(4h), Meeting 2 (3.5h)
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|Richard Farla
|Richard Farla
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|Meeting 1 (2h), Simulation: target patches (4h)
|Meeting 1 (2h), Simulation: target patches (4h), Meeting 2 (3.5h)
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|Yash Israni
|Yash Israni
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|Meeting 1 (2h)
|Meeting 1 (2h), Meeting 2 (3.5h)
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|Tessa de Jong
|Tessa de Jong
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|Meeting 1 (1.5h), Specifications (2h), Introduction (1h), USE (1h), Planning and deliverables (30 min), Spelling (30 min), ...
|Meeting 1 (1.5h), Specifications (2h), Introduction (1h), USE (1h), Planning and deliverables (30 min), Spelling (30 min), Meeting 2 (2h)
|-
|-
|Kaj Scholer
|Kaj Scholer
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|Meeting 1 (1h)
|Meeting 1 (1h), Meeting 2 (1h)
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|Pepijn Tennebroek
|Pepijn Tennebroek
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|Meeting 2 (2h)
|}
|}
==References==
==References==

Revision as of 14:27, 23 March 2023

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

“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.

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 robots 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 vine 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 vine 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 robots 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 urban 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?

Project planning and deliverables

Week Milestones
Week 1 Brainstorm, topic, problem identification, planning, state-of-the-art literature research
Week 2 Further literature study, user analysis, MoSCoW, research for simulation possibility, research sesnors
Week 3 Further literature study, start simulation, research localization methods, research pathfinding methods, further research sensors, complete user analysis
Week 4 Work on simulation, further research localization and pathfinding methods, rewrite MoSCoW, research Vine robot specifications
Week 5 Work on simulation, rewrite simulation goal, further research Vine robot specifications, further research sensors
Week 6 Work on simulation, complete simulation specifications and test cases, complete sensor research
Week 7 Finalize simulation, gather results simulation
Week 8 Complete wiki and presentation

Who is doing what?

Names Tasks
Clinton Emok Sensors, localization and simulation
Richard Farla Simulation environment
Yash Israni Simulation algorithm
Tessa de Jong Literature research and USE
Kaj Scholer Sensors and localization
Pepijn Tennebroek Literature Research and USE

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. For the first query on Reddit several people responded, 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 the technology is expensive. The equipment that is used is expensive as is the training that the people have to have had for using their equipment. The second query on Reddit received one answer of an USAR search specialist. This specialist mentions 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. Furthermore, replacing human rescuers or search dogs with a vine robot will put less danger on them. Lastly, the vine robot will be able to go further in the debris without endangering itself. So, 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: A small vine robot can navigate through tight spaces more easily than larger robots, allowing it to search for survivors in areas that might be otherwise be inaccessible.
  • Diameter: The diameter of the robot that is chosen should be small enough to enable an air compressor to quickly fill the expanding volume of the body while facilitating growth also at low pressure. In research, the main body tube diameter of the robot is 5 cm (Coad et al., 2019).
  • Length: The robot body can grow as the fluid pressure inside the body is higher in comparison to the outside (Blumenschein, 2020). In this research, the soft robot’s body length was 10 meters.
  • Material: For the vine robot to be lightweight and flexible, the materials must share these properties.
    • Soft and flexible materials such as silicone or rubber can be used to mimic the flexibility of a vine. These materials can be easily deformed and are able to conform to complex shapes.
    • Carbon fiber can be used to the create the structural stability of the vine robot. Carbon fiber is a lightweight and strong material providing a high strength-to-weight ratio make it ideal for this application
  • Weight: The vine robot should be lightweight, so that it can be easily transported to the search site and placed into position by the rescue team. Additionally this provides the possibility to deploy the robot in unstable environment as it will not add significant stress to the collapsed structure.
  • 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, additional 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).
  • Turn radius: In research, a vine robot was able to round a 90 degree turn (Coad et al., 2019). From the picture that was added to the paper, it is concluded that the turn radius is bigger than 10 centimeters.

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.

Types of Sensors:

  • Thermal Imaging: Thermal imaging sensors detect the infrared radiation emitted by objects and people. They can be used to detect the heat signature of a person in low-light or obscured environments, making them valuable for search and rescue missions. They are particularly useful for identifying the location of a person who may be trapped in a building, as they can detect body heat through walls and other barriers.
  • Gas Detector: Gas detectors are used to detect the presence of various gases in the air, such as carbon monoxide, methane, and hydrogen sulfide. In a search and rescue situation, gas detectors can be used to detect toxic gases that may pose a danger to both rescuers and survivors. They can also be used to locate areas where there may be trapped humans, as humans exhale carbon dioxide which can be detected by a gas detector.
  • Sound Detector: Sound detectors are used to detect sounds, such as human voices or other noises that may indicate the presence of a human. They are useful for locating people who may be trapped or injured and unable to call for help. They can also be used to detect the sounds of people digging or moving debris, which can help rescuers locate survivors.
  • Chemical Sensor: Chemical sensors can detect the presence of chemicals, such as explosives or hazardous materials, in the air. They can be used to locate areas where there may be hazardous materials that could pose a threat to rescuers or survivors. Chemical sensors can also be used to detect the presence of substances that may be released by a trapped human, such as sweat or other bodily fluids.
  • Light Detection and Ranging (LiDAR): LiDAR sensors use lasers to detect and measure distances to objects. They can be used to create 3D maps of indoor or outdoor environments, which can help rescuers identify potential hazards and locate survivors. LiDAR can also be used to detect movement, such as a person waving their arms or walking, which can help rescuers locate survivors who may be hidden from view.
  • Global Positioning System (GPS): GPS sensors use satellites to determine the location of a person or object. They can be used to track the movement of rescuers and survivors, which can help rescuers locate survivors who may be moving or disoriented. GPS can also be used to create maps of the search area, which can help rescuers identify potential hazards and navigate to areas where survivors may be located.
  • Magnetometer: Magnetometers detect changes in magnetic fields, which can be used to locate metal objects or structures. In a search and rescue situation, magnetometers can be used to locate objects, such as cars or building structures, that may be trapping or hiding humans. Magnetometers can also be used to detect metal objects that may be part of a trapped person's clothing or equipment.
  • Infrared Sensor: Infrared sensors detect infrared radiation, which is emitted by objects and people. They can be used to detect the presence of a person in low-light or obscured environments, making them valuable for search and rescue missions. Infrared sensors can also be used to detect the heat signature of a person's breath or heartbeat, which can help rescuers locate people who may be unconscious or trapped.
Will be completed on Monday/Tuesday with sources
Sensor Type Range Resolution Accuracy Durability Ease of Use Cost Ranking
Thermal Imaging
Gas Detector
Chemical Sensor
Light Detection and Ranging (LiDaR)
Global Positioning System (GPS)
Magnetometer
Infrared Sensor

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 through 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 looking at the table provided, the use cases can be seen 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. This is a good start to figure out what technologies are needed to research. Provided below is some information about them, but each would need to be researched in depth. 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.

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 customized 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, it is believed 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, the assumption for maneuverability 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 it is expected that this will be the standard level of maneuverability 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 it is not desired that they can cross each other either. Thus by saving and relaying its path, resources can be saved (vine robots don’t traverse the same path) and it can be prevented that cross or crash 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. Some design decisions were made where it may not be directly apparent as to why they were chosen. Therefore, these design choices are explained 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, it is known 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.


Simulation Scenario

In active use the robot has to guide rescuers to possible locations of survivors in the environment. This scenario can be described in PEAS as:

  • Performance Measure: The performance measure for the vine robot in the simulation would be the number of survivors found within a given time frame.
  • Environment: The enviroment for the vine robot in the simulation would be a disaster zone with multiple clusters of debris. The debris can be of varying sizes and shapes and may obstruct the robot's path.
  • Actuators: The actuators for the vine robot in the simulation would be the various robotic mechanisms that enable the robot to move and interact with its enviroment.
  • Sensors: The sensors for the vine robot in the simulation would include a set of cameras and microphones to capture diffferent stimuli. Additionally, the robot would also have sensors to detect obstacles in its path.


Environment description:

  • Partially observable
  • Stochastic
  • Collaborative
  • Single-agent
  • Dynamic?
  • Sequential?

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 10.5h 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 5.75h 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 8.5h Meeting 1 (2h), State-of-the-art (3h), USE (3h), Meeting 2 (30min),
Kaj Scholer 7.75h Meeting 1 (2h), Meeting 2 (30min), Problem statement (2h), Specifications (3h), 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 4.5h Meeting 2 (2h), Meeting 2.5 (0.5h), Specification Vine Robot (2h)
Richard Farla 7.5h 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 6.5h Meeting 1.5 (1h), Meeting 2 (2h), Meeting 2.5 (0.5h), Simulation (3h)
Tessa de Jong 7h Meeting 1 (1h 30min), Reddit posts (30 min), Meeting 2 (2h), Rewriting Wiki (3h)
Kaj Scholer 8.75h Meeting 1 (1h 30min), Meeting 2 (2h), Sensor research (3h 30min), Spell Check + Wiki Edit (1h), Adjusting References (45min)
Pepijn Tennebroek 5.5h Meeting 1 (1h 30min), Meeting 2 (2h), Specifications (2h)
Name Total Breakdown week 6
Clinton Emok Meeting 1 (2h), PEAS (2h), Simulation(4h), Meeting 2 (3.5h)
Richard Farla Meeting 1 (2h), Simulation: target patches (4h), Meeting 2 (3.5h)
Yash Israni Meeting 1 (2h), Meeting 2 (3.5h)
Tessa de Jong Meeting 1 (1.5h), Specifications (2h), Introduction (1h), USE (1h), Planning and deliverables (30 min), Spelling (30 min), Meeting 2 (2h)
Kaj Scholer Meeting 1 (1h), Meeting 2 (1h)
Pepijn Tennebroek Meeting 2 (2h)

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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).


"Part of what makes a rescue expensive - that few mention - is for operators to maintain currency in their respective roles.

I know that everywhere is different, and each location may have their own way of doing things, but where I am there are governing bodies that require core efficiencies to be maintained a certain number of hours per year.

Each type of rescue; USAR, BSAR, Flood rescue, vertical rescue et al, require that key elements are trained and tested regularly.

This requires an enormous amount of time and money.

As far as technology goes, each unit will be different.

Vertical will require that their vortex (or which ever system) is maintained

Flood will require boats and ark-angles, GPS, underwater cameras et al.

Our USAR and BSAR require FLIR systems, MPD, strokes and mules, countless items.

The list goes on.

It’s also worth noting that much of the time, a rescue will require multiple agencies. You may have police, Sherrifs, specialist paramedics, parks officers, fire et al. Each one if these with their own kit and technology.

If it becomes a multi day rescue then there is the potential for up to a dozen vehicles to be utilised during that time.

The costs add up." (Foxtrot841, 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).