Development of Search‐and‐rescue Robots for Underground Coal Mine Applications

Rescue missions after coal mine accidents are highly risky and sometimes impossible for rescuers to perform. To decrease the risk to rescuers, two generations of tracked mobile robots have been designed and developed to replace the rescuers. In this paper, we present the design iterations with experiments carried out in training sites for rescuers and in working coal mines, and we summarize the design and development experiences of the mobile robots for such rescue missions. In coal mine rescue robots, the explosion‐proof and waterproof designs are adapted to the explosive and wet environments, while the suspension systems are adapted to the unstructured working environments. The design and development experiences may provide a reference for designing and developing future mobile robot systems for coal mine accident rescue missions.     

Evolving controllers for autonomous robot search teams

Deploying autonomous robot teams instead of humans in hazardous search and rescue missions could provide immeasurable benefits. In such operations, rescue workers often face environments where information about the physical conditions is impossible to obtain, which not only hampers the efficiency and effectiveness of the effort, but also places the rescuers in life-threatening situations. These types of risk promote the potential for using robot search teams in place of humans. This article presents the design and implementation of controllers to provide robots with appropriate behavior. The effective utilization of genetic algorithms to evolve controllers for teams of homogeneous autonomous robots for area coverage in search and rescue missions is described, along with a presentation of a robotic simulation program which was designed and developed. The main objective of this study was to contribute to efforts which attempt to implement real-world robotic solutions for search and rescue missions.     

Using Virtual Pheromones and Cameras for Dispersing a Team of Multiple Miniature Robots

To safely and efficiently guide personnel of search and rescue operations in disaster areas, swift gathering of relevant information such as the locations of victims, must occur. Using the concept of ‘repellent virtual pheromones’ inspired by insect colony coordination behaviors, miniature robots can be quickly dispersed to survey a disaster site. Assisted by visual servoing, dispersion of the miniature robots can quickly cover an area. An external observer such as another robot or an overhead camera is brought into the control loop to provide each miniature robot estimations of the positions of all of the other near-by robots in the robotic team. These miniature robots can then move away from the other near-by robots on the team, resulting in the robot collective becoming swiftly distributed through the local area. The technique has been simulated with differing pheromone persistence levels and implemented using the miniature Scout robots, developed by the Center for Distributed Robotics at the University of Minnesota, which are well-suited to surveillance and reconnaissance missions.     

Human-robot teaming for search and rescue

This work establishes an architecture for Urban Search and Rescue and a methodology for mixing real-world and simulation-based testing. A sensor suite and sensor fusion algorithm for robust victim detection permits aggregation of sensor readings from various sensors on multiple robots. We have embarked on a research program focusing on the enabling technologies of effective USAR robotic rescue devices. The program is also researching system-level design, evaluation, and refinement of USAR rescue architectures that include teams of sensor-laden robots and human rescuers. In this paper, we present highlights from our research, which include our multiagent system (MAS) infrastructure, our simulation environment, and our approach to sensor fusion and interface design for effective robotic control.     

Emergency response to the nuclear accident at the Fukushima Daiichi Nuclear Power Plants using mobile rescue robots

On March 11, 2011, a massive earthquake (magnitude 9.0) and accompanying tsunami hit the Tohoku region of eastern Japan. Since then, the Fukushima Daiichi Nuclear Power Plants have been facing a crisis due to the loss of all power that resulted from the meltdown accidents. Three buildings housing nuclear reactors were seriously damaged from hydrogen explosions, and, in one building, the nuclear reactions became out of control. It was too dangerous for humans to enter the buildings to inspect the damage because radioactive materials were also being released. In response to this crisis, it was decided that mobile rescue robots would be used to carry out surveillance missions. The mobile rescue robots needed could not be delivered to the Tokyo Electric Power Company (TEPCO) until various technical issues were resolved. Those issues involved hardware reliability, communication functions, and the ability of the robots' electronic components to withstand radiation. Additional sensors and functionality that would enable the robots to respond effectively to the crisis were also needed. Available robots were therefore retrofitted for the disaster reponse missions. First, the radiation tolerance of the electronic componenets was checked by means of gamma ray irradiation tests, which were conducted using the facilities of the Japan Atomic Energy Agency (JAEA). The commercial electronic devices used in the original robot systems operated long enough (more than 100 h at a 10% safety margin) in the assumed environment (100 mGy/h). Next, the usability of wireless communication in the target environment was assessed. Such tests were not possible in the target environment itself, so they were performed at the Hamaoka Daiichi Nuclear Power Plants, which are similar to the target environment. As previously predicted, the test results indicated that robust wireless communication would not be possible in the reactor buildings. It was therefore determined that a wired communication device would need to be installed. After TEPCO's official urgent mission proposal was received, the team mounted additional devices to facilitate the installation of a water gauge in the basement of the reactor buildings to determine flooding levels. While these preparations were taking place, prospective robot operators from TEPCO trained in a laboratory environment. Finally, one of the robots was delivered to the Fukushima Daiichi Nuclear Power Plants on June 20, 2011, where it performed a number of important missions inside the buildings. In this paper, the requirements for the exploration mission in the Fukushima Daiichi Nuclear Power Plants are presented, the implementation is discussed, and the results of the mission are reported.     

A semantically-informed multirobot system for exploration of relevant areas in search and rescue settings

Coordinated multirobot exploration involves autonomous discovering and mapping of the features of initially unknown environments by using multiple robots. Autonomously exploring mobile robots are usually driven, both in selecting locations to visit and in assigning them to robots, by knowledge of the already explored portions of the environment, often represented in a metric map. In the literature, some works addressed the use of semantic knowledge in exploration, which, embedded in a semantic map, associates spatial concepts (like ‘rooms’ and ‘corridors’) with metric entities, showing its effectiveness in improving the total area explored by robots. In this paper, we build on these results and propose a system that exploits semantic information to push robots to explore relevant areas of initially unknown environments, according to a priori information provided by human users. Discovery of relevant areas is significant in some search and rescue settings, in which human rescuers can instruct robots to search for victims in specific areas, for example in cubicles if a disaster happened in an office building during working hours. We propose to speed up the exploration of specific areas by using semantic information both to select locations to visit and to determine the number of robots to allocate to those locations. In this way, for example, more robots could be assigned to a candidate location in a corridor, so the attached rooms can be explored faster. We tested our semantic-based multirobot exploration system within a reliable robot simulator and we evaluated its performance in realistic search and rescue indoor settings with respect to state-of-the-art approaches.     

Localization of emergency acoustic sources by micro aerial vehicles

For micro aerial vehicles (MAVs) involved in search and rescue missions, the ability to locate the source of a distress sound signal is significantly important and allows fast localization of victims and rescuers during nighttime, through foliage and in dust, fog, and smoke. Most emergency sound sources, such as safety whistles and personal alarms, generate a narrowband signal that is difficult to localize by human listeners or with the common localization methods suitable for broadband sounds. In this paper, we present three methods for MAV‐based emergency sound localization system. The first method involves designing a new emergency source for immediate localization by the MAV using a common localization method. The other two novel methods allow localizing the currently available emergency sources, or other narrowband sounds in general, that are difficult to localize due to the periodicity in the sequence of sound samples. The second method exploits the Doppler shift in the sound frequency, caused due to the motion of the MAV and the dynamics of the MAV to assist with the localization. The third method involves active control of the robot's attitude and fusing acoustic and attitude measurements for achieving accurate and robust estimates. We evaluate our methods in real‐world experiments with real flying robots.     

Exploration strategies based on multi-criteria decision making for searching environments in rescue operations

Some applications require autonomous robots to search an initially unknown environment for static targets, without any a priori information about environment structure and target locations. Targets can be human victims in search and rescue or materials in foraging. In these scenarios, the environment is incrementally discovered by the robots exploiting exploration strategies to move around in an autonomous and effective way. Most of the strategies proposed in literature are based on the idea of evaluating a number of candidate locations on the frontier between the known and the unknown portions of the environment according to ad hoc utility functions that combine different criteria. In this paper, we show some of the advantages of using a more theoretically-grounded approach, based on Multi-Criteria Decision Making (MCDM), to define exploration strategies for robots employed in search and rescue applications. We implemented some MCDM-based exploration strategies within an existing robot controller and we evaluated their performance in a simulated environment.     

Semi-autonomous serially connected multi-crawler robot for search and rescue

In this paper, we develop a semi-autonomous serially connected multi-crawler robot for search and rescue. In large-scale disasters, such as earthquakes and tornadoes, the application of rescue robots to search for survivors under rubble would be beneficial. Snake-like robots (robots composed of serially connected units) are an effective candidate for such robots. Their long body enables them to overcome obstacles, and they can move into narrow spaces because of their thin shape. However, conventional snake-like robots have significant problems with operability. The numerous degrees of freedom of their bodies require complex operation to overcome obstacles, and training is required for the operators. Thus, survivors or community members cannot operate conventional robots to search for victims, despite the availability of such rescue robots. Here, we address this problem and develop a semi-autonomous serially connected multi-crawler robot designed for non-trained operators, such as community members or rescued survivors. It can be controlled easily by a conventional two-channel user interface with levers for turning and straight line motion. To demonstrate the effectiveness of our proposed mechanism, a prototype robot was developed and experiments were conducted. The results confirm that the proposed robot had both higher operability and higher mobility than conventional robots.     

An Initial Evaluation of Approaches to Building Entry for Large Robot Teams

Teams of robots offer potential reductions in risk for rescuers and improved rescue rates for search and rescue in collapsed buildings and other restricted environments. However, one aspect of deployment of such teams that is often overlooked is the initial entry of the robots into the building. If many robots enter the building from the same entrance, they are likely to interfere with each other and dramatically slow the initial phase of exploration. In this paper, we use a low fidelity simulation to evaluate several approaches to overcoming this initial congestion and identify heuristics that might allow the robots to most quickly clear the entry area and begin their actual mission. Our results show that unless the exits to the initial entry area are small, over a wide range of parameters, the most effective technique was for every robot to move in the direction of the longest open space it senses. In more cluttered environments with smaller exits, wall following, a strategy less dependent on the quality of sensing, proved more effective. Informal comparisons of these algorithms in a high fidelity simulation with limited trials and no variation in parameters suggested that simply promoting dispersion might be a more effective strategy for realistically complex dynamics.     

Snake-Like Robot for Rescue Operations — Proposal of a Simple Adaptive Mechanism Designed for Ease of Use

Rescue operations are one of most effective applications for robots and various rescue robots operated by rescue staff have been developed. However, in large-scale disasters, there is a significant problem, i.e., a shortage of operators. In this paper, we consider this problem and propose a snake-like rescue robot which is designed for non-professional volunteer operators. To realize the rescue robot simply, we focus on mechanical design, and realize usability by utilizing properties of its body and the real world. Experiments have been carried out to demonstrate the effectiveness of the proposed robot.     

基于机器视觉的自主式救援机器人的研究

本文将面向自主式救援机器人,从现阶段日本、中国对自主式救援机器人研究现状出发,深入分析自主式救援机器人的功能需求和硬件设备需求,并且结合自主式救援机器人工作中所具备的功能进行研究。在灾害事故当中,由于环境复杂救援人员难以勘探真实的灾害环境,从而影响救援效果,而自主式救援机器人则能够通过自身强大的移动、远程通信、监测与跟踪等功能为救援人员提供帮助。面对灾害事故频发的现代化社会,救援机器人的研发已成为全球重要的研究事项。     

多层建筑应急疏散仿真

以多层建筑为背景, 研究应急疏散问题, 基于改进的路径规划算法, 并将多智能体技术应用在模型间的通信交流上. 采用机器人感知周围环境, 通过设置机器人个数以及初始位置, 对灾情中室内被困人员进行智能搜救, 并采集现场实时数据, 作出决策分析. 机器人实时感知现场状况的变化, 引导人员疏散, 并将实时数据传输给施救人员, 采取进一步救援措施. 结果表明, 该三维仿真技术为有效减少人员疏散中的伤亡和最佳救援方案的制定提供了参考, 具有一定的现实指导意义.     

援潜救生作业仿真演示系统

援潜救生是一个必要而又十分艰难复杂系统工程,由于水下环境的复杂性,对失事潜艇实施援潜救生作业,被称为三级援救的作业,包括搜索、观察失事潜艇,向艇员提供生存保障和使用深潜救生艇将艇员救离失事潜艇.文中针对失事艇的救援活动提出了一个完整的援潜救生作业仿真演示系统,介绍了该系统物理环境的设计和各子系统的功能,完成了援潜救生的作业程序三步骤下救生过程的多维仿真演示过程,为指挥决策者提供了生动、直观的多维视觉表现.     

Multirobot exploration for search and rescue missions: A report on map building in RoboCupRescue 2009

In the future, mobile robots may be able to assist rescue crews in search and rescue missions that take place in the dangerous environments that result from natural or man‐made disasters. In 2006, we launched a research project to develop mobile robots that can rapidly collect information in the initial stages of a disaster. One of our important objectives is three‐dimensional (3D) mapping, which can be a very useful tool for assisting rescue crews in strategizing rescue missions. To realize this 3D mapping, we identified five issues that we needed to address: (1) autonomous traversal of uneven terrain, (2) development of a system for the continuous acquisition of 3D data of the environment, (3) coverage path planning, (4) centralization of map data obtained by multiple robots, and (5) fusion of map data obtained by multiple robots. We solved each problem through our joint research. Each research institute in our group took charge of solving one of the above issues according to its area of expertise. We integrated these solutions to perform 3D mapping using our tracked vehicle, Kenaf. To validate our integrated autonomous 3D mapping system, we participated in RoboCupRescue 2009 and demonstrated our system using multiple robots on the RoboCupRescue field. In this paper, we introduce our mapping system and report the mapping results obtained at the RoboCupRescue event. © 2011 Wiley Periodicals, Inc.     

Robot Teams for Intervention in Confined and Structured Environments

Safety, security, and rescue robotics can be extremely useful in emergency scenarios such as mining accidents or tunnel collapses where robot teams can be used to carry out cooperative exploration, intervention, or logistic missions. Deploying a multirobot team in such confined environments poses multiple challenges that involve task planning, motion planning, localization and mapping, safe navigation, coordination, and communications among all the robots. To complete their mission, robots have to be able to move in the environment with full autonomy while at the same time maintaining communication among themselves and with their human operators to accomplish team collaboration. Guaranteeing connectivity enables robots to explicitly exchange information needed in the execution of collaborative tasks and allows operators to monitor and teleoperate the robots and receive information about the environment. In this work, we present a system that integrates several research aspects to achieve a real exploration exercise in a tunnel using a robot team. These aspects are as follows: deployment planning, semantic feature recognition, multirobot navigation, localization, map building, and real‐time communications. Two experimental scenarios have been used for the assessment of the system. The first is the Spanish Santa Marta mine, a large mazelike environment selected for its complexity for all the tasks involved. The second is the Spanish‐French Somport tunnel, an old railway between Spain and France through the Central Pyrenees, used to carry out the real‐world experiments. The latter is a simpler scenario, but it serves to highlight the real communication issues.     

Simulation and control of distributed robot search teams

This article describes the simulation of distributed autonomous robots for search and rescue operations. The simulation system is utilized to perform experiments with various control strategies for the robot team and team organizations, evaluating the comparative performance of the strategies and organizations. The objective of the robot team is to, once deployed in an environment (floor-plan) with multiple rooms, cover as many rooms as possible. The simulated robots are capable of navigation through the environment, and can communicate using simple messages. The simulator maintains the world, provides each robot with sensory information, and carries out the actions of the robots. The simulator keeps track of the rooms visited by robots and the elapsed time, in order to evaluate the performance of the robot teams. The robot teams are composed of homogenous robots, i.e., identical control strategies are used to generate the behavior of each robot in the team. The ability to deploy autonomous robots, as opposed to humans, in hazardous search and rescue missions could provide immeasurable benefits.     

Trial by fire [rescue robots]

On September 11, 2001, the Center for Robot-Assisted Search and Rescue (CRASAR) responded within six hours to the World Trade Center (WTC) disaster; this is the first known use of robots for urban search and rescue (USAR). The University of South Florida (USF) was one of the four robot teams, and the only academic institution represented. The USF team participated onsite in the search efforts from 12-21 September 2001, collecting and archiving data on the use of all robots, in addition to actively fielding robots. This article provides an overview of the use of robots for USAR, concentrating on what robots were actually used and why. It describes the roles that the robots played in the response and the impact of the physical environment on the platforms. The quantitative and qualitative performance of the robots are summarized in terms of their components (mobility, sensors, control, communications, and power) and within the larger human-robot system. Lessons learned are offered and a synopsis of the current state of rescue robotics and activities at the CRASAR concludes the article.     

Rats, robots, and rescue

In early May, media inquiries started arriving at my office at the Center for Robot-Assisted Search and Rescue (www.crasar.org). Because I'm CRASAR's director, I thought the press was calling to follow up on the recent humanitarian award given to the center's founder, John Blitch, for successfully using small, backpackable robots at the World Trade Center disaster. Instead, I found they were asking me to comment on the "roborats" study in the 2 May 2002 Nature. In this study, rats with medial force brain implants underwent operant conditioning to force them into a form of guided behavior, one aspect of which was thought useful for search and rescue. The article's closing comment suggested that a guided rat could serve as both a mobile robot and a biological sensor. Although a roboticist by training, I'm committed to any technology that will help save lives while reducing the risk to rescuers. But rats?.     

A Building Information Model enabled Multiple Traveling Salesman Problem for building interior patrols

During building emergencies, an effective and visible primary search plan enhances situation awareness and enables a more efficient rescue mission. The aim of the primary search during an emergency is the rapid screening of every space in the building to identify locations of victims and their conditions. Afterwards, first responders can plan for the rescue of those victims. To provide a timely draw up of interior patrol routes and assign rescue teams to conduct the primary search, this study formulates the problem as a multiple traveling salesman problem (M-TSP) where the comprehensive building interior network is given by the building information models (BIMs), while the total traveling costs (lengths) of every rescue team is minimized. To meet the requirement of real-time patrol routes optimization, we employed the branch-and-price algorithm for the enhancement of computation efficiency. In addition, a heuristic method was introduced to provide timely solutions for large-scale networks. A case study is conducted for a single-floor convention center. We utilized BIM to construct a network of nodes and arcs where the decision model requires as input, and the branch-and-price algorithm finds the optimal patrol. The resulting patrol routes can be visualized and serve as guide for rescue teams to conduct the primary search. The integrated approach proposed in this study is practical and can expedite search and rescue missions.