New technologies are advancing and emerging day by day to improve the safety of humans by making use of various autonomous technologies. The continuous utilization of autonomous vehicles/systems in search and rescue (SAR) operations is a challenging research area particularly for marine-based activities. A comprehensive systematic literature review (SLR) providing an overview of improvisations that have been done in the field of autonomous technologies for search and rescue operation over the last five years has been compiled in this paper. A methodology for using autonomous vehicles in water for SAR operations has been incorporated and demonstrated. The focus of this study is to look at the various techniques and address different challenges faced for human beings’ safety during rescue operation. The comparison of results achieved for various technologies and algorithms is highlighted in this paper. This literature survey proves to be a good source of information for fellow researchers to precisely analyze the study results.
The response to any mishaps should be made in such a way that the victims are reached as soon as possible along with taking care to avoid additional collapse and damage. The challenging part is that the victims and the rescuers should both be safe; the foremost and primary goal is to save lives. In this world of emerging technologies and automation, robots can prove to be a useful asset to meet this goal either by interacting directly or indirectly with victims or by supporting protection equipment. The main task of the rescue team is to search for the human survivors on the incident site, and it is a hazardous task that often leads to the loss of lives. However, the introduction of autonomous robotic rescue [
For centuries, the biggest fear of people was the possibility of falling into water bodies. Presently, several different technologies solve this problem. Although there is plenty of protection equipment like trailing lines, man overboard detection transmitters, chase boats, rescue buoys, and life rings to provide safety, a significant drawback of these devices is that they work only in some specific situations. Due to human limitations or rescue equipment drawbacks, a new device or product is needed to save the lives of people who work in the accident-prone marine area. Due to large ships’ movement and their ongoing trade, supervising and protecting staff on board are difficult.
In this paper, the newest advancements and techniques in the field of autonomous technologies for search and rescue operation that have proved fruitful are reviewed and incorporated. The work in this paper would help other fellow researchers to find more innovative and precise methodologies to achieve desirable results.
This paper is organized as follows. Section
In today’s world, where data is viewed as the “new oil,” SLR has proven to be of great help to researchers all over the world. Sometimes, it may become a little overwhelming to consume all the data currently existing for a specific domain. There is enormous data and literature in the field of autonomous robotic rescue vehicles, so it becomes a little difficult to summarize and stay updated with the newest methodologies and technologies because very few SLRs have been conducted in this field until now. With this domain gaining popularity, it is necessary to conduct a literature review, so the authors of this paper have analyzed the research in this domain for the past five years using the six most popular digital libraries. The search questions were formulated, and then the results were combined with the critical challenges faced during the review process.
Digital libraries these days are the most used and reliable source for books, journals, and various articles from scholars and researchers worldwide. In this literature review, six renowned digital libraries have been considered. Following are the digital libraries that have been used to extract data: Science Direct Springer Research Gate IEEE Web of Science (WoS) arXiv
The review in this paper has been restricted to the studies done during the last five years, i.e., from 2016 to 2020.
It is essential to precisely understand what questions would be answered in this paper after doing the complete literature review. The questions have been formulated so that the answers obtained after each question are accurate and precise and have no unnecessary information. The following questions have been answered: Techniques used in autonomous vehicles for communication between the command center and the victim Challenges in autonomous rescue boat Navigation of the rescue boat to the desired location
To get familiar with autonomous robotic rescue boat, a quick review of some articles falling under this topic was done. Some popular models and methodologies under this topic that are correct and relevant, which would help us research, have been considered. The different search query questions and the number of research papers found in each of the six digital libraries are shown in Figures
Results from the search query “specific components required for autonomous boat functioning.”
Results from the search query “techniques used in autonomous robotic rescue boat.”
Results from the search query “challenges in autonomous rescue boat.”
Results from the search query “navigation of rescue boat to the desired location.”
In paper [
The authors of [
The noises generated due to high camera vibration of autonomous vehicle caused by waves and less robust lighting lead to failing obstacle detection, low camera quality, and slow processing, resulting in blurry images and deteriorating the autonomous robotic rescue vehicle navigation. To overcome these problems, the authors of [
The algorithms discussed in [
The scenario during a disaster is often unpredictable, unstructured, and time varying, which means that there are many challenges for the successful implementation of the unmanned vehicle [
These days, a wide variety of autonomous vehicles are used for different operations in many different fields, and this number is going to increase in the subsequent years. Many large-scale systems aim to solve these problems, but they are quite costly and not very useful too. Research has been done focusing on the interaction between these systems and implementing various operations [
The authors of [
The papers [
Recent studies [
The search and rescue operations are not friendly; they can be deployed quickly [
From past research works, robotic tools have been widely improving for search and rescue operations, but some flaws restrict the full usage of these systems without human intervention [
Recently, there is growth in the research of USVs. More numbers of USV vehicles have been used in various operations like those in the military. The limitation of [
Unmanned aerial vehicles (UAVs) [
Nowadays, unmanned aerial vehicles are being used to view the infected area, but there is a significant collision concern [
The authors of [
This section shows an overview of an unmanned surface vehicle (USV) and the interaction of all subsystems with each other. Each subsystem comprises various devices that perform the required tasks for the proper functioning of the overall system. Figure
Architecture of the system for search and rescue operation.
The hardware module consists of majorly different components, namely, Arduino, motor driver, motors, power supply, global positioning system (GPS) module, camera, Raspberry Pi, and RF module. These components are configured for the overall functioning of the system.
The GPS is used for defining the global position of an object. Different modules of GPS have been compared for better understanding. Table
Different GPS modules.
Types of modules | Chipset used | Updating rate (Hz) |
---|---|---|
LS23060 [ | MediaTek MT3318 | 5 |
EM-406A [ | SiRF Star III | 1 |
SUP500F [ | Venus 634 | 10 |
Copernicus [ | Trimble TrimCore | 1 |
DS2523T [ | u-blox 5 | 4 |
There have been three generations of Raspberry Pi, and every generation has two models, namely, Model A and Model B. The characteristics of both models of Raspberry Pi along with the little deviation in the model are depicted in Figures
Raspberry Pi model vs. number of cores.
Raspberry Pi model vs. number of GPIO pins.
The motor drivers used in the system for search and rescue are mainly four types, i.e., AC, DC, servo, and stepper. The choice of motor driver depends on its application and usage. Motor drivers can be controlled directly by connecting the power supply or by devices such as wireless systems and microcontrollers.
DC motor drivers are widely used in many applications due to their enormous advantages. Figure
Motor supply voltage vs. efficiency.
Motor supply voltage vs. revolving speed.
From automobiles and robotics, small- and medium-sized motoring applications often feature DC motors for their wide range of functionality. Because DC motors are deployed in such a wide variety of applications, there are different types of DC motors suited to different tasks across the industrial sector. Different types of DC motors are classified in Figure
Different types of DC motors.
The RF module is used for transmitting and receiving the message signals. It is essential and crucial part of the search and rescue system. A drone can be programmed in such a way that it is capable of sending information such as the location of itself and images of victim to the receiver using RF module wherever it detects any victim face that has fallen in the water and needs help. Figure
Different types of RF modules.
There are many face detection techniques in the literature. The authors of this paper have studied the five most efficient and popular face detection techniques to detect the face of the victim which are shown in Figure Haar-like feature-based face detection Haar cascade algorithm is a machine learning-based algorithm used for detecting objects. The authors in [104 and references therein] have proposed a model to improve the performance of this algorithm. It is done in two steps: Firstly, new features have been defined, also called separate features, for the detector, which adds the do-not-care area between the Haar features, and hence a new feature for the cascade detector can be defined. Secondly, they have improved the detection rate by using the decision algorithm, selecting the best width of the do-not-care area. In this algorithm, the background images are ignored, and left stages are not calculated when the stage rejects an image. However, if the false detection occurs in a stage, it affects the other stages, resulting in unwanted increase in the false rate, which is its main limitation. Geometric based face detection The principal component analysis of face structure modeling is discussed in the paper ([ Improved LBP algorithm Local binary pattern (LBP) is a face detection technique ([ Face detection based on Viola–Jones algorithm applying composite features The Viola–Jones algorithm is a face detection algorithm that instantly and precisely detects objects in images and works exceptionally well with the human face ([ Firstly, from an input image, the human face is detected in a rectangular frame with the help of the Viola–Jones algorithm. Then, the faces present in the rectangle-shaped frame are calibrated, and after that they are processed into four types of subimages. Following that, NLDA (zero space linear discriminant analysis) is used to extract the features obtained from the complete facial picture and four subpictures. Then, all extracted features (local features and global features) are calculated with the discriminant length. Lastly, regions with considerable distance from discriminant values are selected to obtain the latest compound feature vectors. After that, the input is given for face recognition to the classifier. The original Viola–Jones algorithm showed several undetected and false face detection. The main disadvantage of using this method is that it takes a long time to train the model. Secondly, it has reduced NIR detection capability (near-infrared-based face detection) as the distance is increased. It is tested on single face frontal images only. However, the method described in this paper has lower false detection rate and missed detection rate compared to the Viola–Jones algorithm. Face detection using improved faster R-CNN Face detection using deep learning CNN is a rapidly growing technology offering different generations like R-CNN and Fast CNN to compute the accurate result in a limited time. The authors of the paper ([ The five most popular and widely used face detection techniques which have been described are compared on the basis of different parameters in Table
Types of face detection algorithms.
Comparison of different face detection techniques.
Parameter | Haar cascade algorithm [ | Geometric based Algorithm [ | Viola–Jones algorithm with composite features [ | Improved LBP algorithm [ | Faster R-CNN algorithm [ |
---|---|---|---|---|---|
Precision | Low | Low | Very high | High | Highest |
Execution time | High | High | Low | Low | Low |
Learning time | High | High | Low | High | Low |
Ratio between detection rate and false alarm | High | Low | High | High | Very high |
Merits and demerits of various face detection techniques.
Techniques | Merits | Demerits |
---|---|---|
Haar cascade algorithm [ | Lesser false alarm part; improved feature extraction | Complex to implement |
Geometric based algorithm [ | Effective approach; easy implementation | Low accuracy; more false alarms |
Viola–Jones algorithm with composite features [ | High accuracy rate and low false detection rate | Sensitive to illumination variations |
Improved LBP algorithm [ | Simple to implement | Not robust |
Faster R-CNN algorithm [ | Very high precision | No such demerits for this algorithm |
Navigation can be done with the help of a grid map after all the areas have been inspected. The navigation planner takes into account to steer through the grid map autonomously from one pose to another. The comprehensive planner traces the pathway from the present position to the final position with the help of the A-Star algorithm. In contrast, the local planner generates linear and angular velocities along the global way while avoiding obstacles based on the cost map parameters. The regional planner practices the dynamic window approach (DWA) to inspect the velocities. The investigational node simply presents the poses (x, ROS implementation The ROS platform is basically made for robots made to be operated on the ground, it has navigation techniques for these kinds of robots, and it is inappropriate for UAVs. Nevertheless, the procedure taken by the ROS is an instruction-based procedure. This execution sample gives the robot its control space and predicts the ways which would end up in a close to perfect indoor mapping with the help of an autonomous vehicle. The authors in [ Simulation software All simulations can be performed on the Gazebo software. This Gazebo software has a physics engine which helps us in imitating the real motions of various arrangements of UWSVs and makes it a lot more possible to test in the various kinds of situations. This software is also convenient for adding new sensors, design changes, rapid testing of algorithms, and even quick prototyping. For programming and controlling the USV, robot operating system (ROS) is used. ROS is software that functions as a bridge between some operating system or database and various applications, specifically on a network, for robotics; it therefore provides a software framework which can be used as tool for software development. It therefore provides a large set of libraries which help in providing robots with a primary focus on things such as mobility, perception, and manipulation. It gives us a set of tools with functionalities such as testing, debugging, and envisioning sensor tools and data for networking, multirobot, and other dispersed systems. One more cause for using ROS is its great integration capabilities with the Gazebo simulator. Estimation and control An efficacious Kalman filter [ To get desirable responses such as complex manoeuvres and hovering at a particular place of the aerial vehicle, its parameter for every component can be tuned perfectly to get the desirable output. Other methods for the planning of the path can be executed in the regulatory loop to get a more fluid output from the UAV. These types of software contained in the loop strategy provide us with a larger flexibility in the process of examining the algorithms prior to the real implementation on an actual stage and evade the chance of some kind of injury or damage, at an earlier stage only.
Autonomous rescue boats that are easy to operate are currently being used by a range of scientists and government agencies to provide rescue operations and assistance in the marine bodies. The micro-USVs can be operated autonomously. They can be configured to communicate through a GPS connection that allows data to be disseminated. Communication plays a fundamental role in the rescue operation. Since connectivity is reliant on the environmental conditions that the system is working in, such as the wave conditions and the weather of that area, localization problems related to weak GPS signals may occur, causing communication problems with the boat, and they must not be underestimated. For better communication, several GPS modules have been used to get a precise location. Therefore, localization techniques used are versatile in case of GPS problems. An additional powerful transmitter embedded with the modules can be used for increasing the range of the system and enhancing the capabilities. In addition, the receiver can be tuned in such a way that the distortion caused in the signal from the unwanted signal is reduced, which further can enhance the communication range of the system. Moreover, in GPS modules, LS23060 has good receiving sensitivity. It has speedy positioning time, positional accuracy, power consumption, time accuracy.
The new Raspberry Pi 3 is the fastest model and is quite cheap. It is essentially a minicomputer of small size that can get connected to a TV or a computer monitor, and makes use of any standard mouse and keyboard. It is a small-sized device that is capable of allowing people of any age to traverse through the area of computing and to program in Python language. TB6612 motor driver has outstanding efficiency; it requires 12.02 V supply, with an efficiency of 95.97%, and RPM is also very high among all the motor drivers. This device is a surface-mount chip available in many standard modules, shields for the Arduino and HATs for the Raspberry Pi.
Among face detection algorithms, the Faster R-CNN algorithm is the best due to the highest precision. It has much less execution time, and the learning time is too short. Moreover, the ratio between the detection and the false alarm rate is pretty large. According to these parameters, it is the best.
Implementing the LS23060 GPS module along with Raspberry Pi 3 and Faster R-CNN algorithm could further make the search and rescue boat more effective and reliable.
There has been an addition in the popularity of boating and other marine-based activities. With the increase in the number of people interested in water-related activities, there has been an ample rise in mishaps. Autonomous rescue boats at sea can be started with the minimum support and are an effective way to perform rescue operations. If any incident happens, a quick response is generated by the system to transmit a message to the autonomous robotic rescue boat. Once the boat gets the message, it starts approaching the place the message came from and, thus, rescues the person.
In manual rescue systems, human rescuers put their life at risk to rescue people who fall into water bodies, but an autonomous rescue boat reduces the risk of loss of a human’s life. In a lot of cases, the rescuers die while undertaking the rescue operation. In autonomous robotic rescue boat, even if some damage caused to the rescue boat while rescuing, it will not be much of an issue because it can be repaired. Therefore, autonomous devices are faster, more accurate, and more responsive than manual rescue systems. Moreover, they can perform even under inclement weather conditions and even in the dark. An autonomous rescue system can also be used by Navy during war when manual rescue systems become impractical.
Autonomous rescue system continues to perform even when the duration of operation elongates as compared to manual rescue system which has limitation on its endurance.
Autonomous boats can always be designed to be highly tough and take considerable loads irrespective of the climatic conditions. Their structure and the base provide durability to them on the water even during unfavorable weather conditions. They are provided with all the necessary first aid equipment that would be required for the person being rescued. Thus, autonomous boats provide a more agile and efficient alternative to manual involvement required in a marine rescue operation.
Not only this paper discusses the various contributions that this project can make in various fields, but it is also of a novel importance because of the following factors which make this project unique in its own way. Less human involvement: since it is an automatic boat, manpower required to operate the system is limited Quick response: this system uses an effective way to reach the place of accident Flexibility under all weather conditions; it can withstand various weather extremes and respond accordingly The system can operate over large areas and distances It integrates monitoring system for rescue operation It is based on highly accurate face detection algorithm for better human recognition
Rescue of people from seashores: at the seaside, there are danger zones where life threatening incidents can happen anytime due to high tides or any other activities in the water bodies which can be dangerous. For these incidents, autonomous robotic rescue boats can be deployed at these sites, which are capable of locating the place of accident and then transmitting an alert message to the base station, which then sends the rescue boat to the place of accident.
Military, defence, and coastal security applications: the autonomous robotic rescue boat has the capability to navigate and locate an underwater object of interest and then perform further autonomous manipulations as and when required by the respective authorities.
Patrolling and minesweeping: autonomous rescue boats can be used for detecting and removing naval mines using various mechanisms and keeping the waterway clear for safe shipping during uncertain times like wars.
Natural disaster relief: in case of natural disasters like floods, landslides, and tsunamis, the autonomous robotic rescue boat can be used to detect people who have drowned in the water bodies or have been wounded, and can save thousands of lives.
Environmental monitoring systems: they play a very crucial role in disaster relief by detecting and inspecting the critical underwater infrastructure, measuring the destruction, and recognizing various sources of pollution in the harbors and the fishing areas.
Inspection of disaster damage: the autonomous robotic rescue boat can be used to survey the damage caused by natural disasters like tsunamis with the help of the fitted camera, or it can be further used for rescuing the victims stranded on a vessel which are sinking or have lost the ability to move.
Rescue operations required during water-sport events: with the increase in the number of people interested in water-related activities, the probability of mishap has increased over the years. Autonomous rescue boats can be of great help during these events.
The study of autonomous robotic rescue boat is continuously increasing, and the researchers are still working to make this technology more advanced. In this paper, the autonomous rescue boat and the techniques that are governed are reviewed. Several articles have been studied from 2016 to 2020, showing different methods to rescue a person. The review has been carried out in such a way that the papers are differentiated according to the techniques used, the main challenges in autonomous vehicles, and the navigation of the rescue boat. Some papers depicted the fact that the larger the boat’s size, the more the chances that collisions are small sized. Moreover, the small-sized boat trajectory can be easily controlled, and navigation will not become cumbersome and challenging. However, the effect of waves cannot be ignored, which leads to difficulty in precisely estimating the trajectory of the autonomous rescue boat. The low accuracy of sensors and devices also impacts on the images taken from the cameras. Therefore, researchers have mainly addressed the problems faced for achieving excellent manoeuvrability.
The hardware and software part plays an essential role in designing a better rescue boat. Hardware parts like GPS devices (transmitters and receivers), Raspberry Pi, RF module, motor drivers, motors, batteries, and Arduino along with the intensive use of software parts like face detection and various algorithms make the whole process of rescuing feasible and efficient on time. The ROS platform has been used for the implementation of navigation for ground-based robots, and it simulates the trajectories. A drone is used to navigate the victim and pass the signal via RF module to the autonomous robotic rescue boat. The Gazebo software allows doing the simulation, which has the power to replicate real motions of various arrangements of the autonomous boat in different scenarios. An efficacious Kalman filter is used to combine all the data coming from the sensor from the boat into one navigational dataset to regulate the position and speed of the boat. Further expansion for the development for this project should be focused on getting a motor of even more power for the rescue unit. For even lesser delay, the code can be optimized for better and advanced tracking, as well as better noise reduction capabilities and hopefully increase in the range for the victim’s homing, which can tune the receivers to a greater extent. After all these optimization techniques and modifications are added to the system, the system would become much more effective and reliable for the man overboard rescue operations on the actual field environment. The amount of data would never seize to increase, and new data and information will keep on coming, so all the future studies in this area should take into consideration whether the static models are reliable enough when thinking about long-term application or if lifelong training should be thought of more. This review can help other scientists and researchers that are studying this field and encourage them to gather more data and information for their research analysis.
The authors declare that they have no conflicts of interest.