The current state and future outlook of rescue robotics

Robotic technologies, whether they are remotely operated vehicles, autonomous agents, assistive devices, or novel control interfaces, offer many promising capabilities for deployment in real‐world environments. Postdisaster scenarios are a particularly relevant target for applying such technologies, due to the challenging conditions faced by rescue workers and the possibility to increase their efficacy while decreasing the risks they face. However, field‐deployable technologies for rescue work have requirements for robustness, speed, versatility, and ease of use that may not be matched by the state of the art in robotics research. This paper aims to survey the current state of the art in ground and aerial robots, marine and amphibious systems, and human–robot control interfaces and assess the readiness of these technologies with respect to the needs of first responders and disaster recovery efforts. We have gathered expert opinions from emergency response stakeholders and researchers who conduct field deployments with them to understand these needs, and we present this assessment as a way to guide future research toward technologies that will make an impact in real‐world disaster response and recovery.     

Post‐disaster assessment with unmanned aerial vehicles: A survey on practical implementations and research approaches

In this paper, we provide a review of the principal aspects related to search & rescue (SAR) with unmanned aerial vehicles (UAVs), with particular interest in the phase of post‐disaster assessment (PDA). Some areas of interest related to this topic have been chosen for the analysis: the aerial platforms used in the field, multirobot software architectures, onboard sensors and simultaneous localization and mapping approaches, terrain coverage algorithms, autonomous navigation techniques, and human‐swarm interfaces. All these aspects have been analyzed with respect to the state‐of‐the‐art, and also in relation to the project PRISMA, which focuses on the development and deployment of robots and autonomous systems that can operate in emergency scenarios, with a specific reference to monitoring and real‐time intervention.     

Rescue robotics — a crucial milestone on the road to autonomous systems

Rescue robotics is an important steppingstone in the scientific challenge to create autonomous systems. There is a significant market for rescue robots, which have unique features that allow a fruitful combination of application-oriented developments and basic research. Unlike other markets for advanced robotics systems like service robots, the rescue robotics domain benefits from the fact that there is a human in the loop, which allows a stepwise transition from dumb teleoperated devices to truly autonomous systems. Current teleoperated devices are already very useful in this domain and they benefit from any bit of autonomy added. Human rescue workers are a scarce resource at disaster scenarios. A single operator should, hence, ideally supervise a multitude of robots. We present results from the rescue robots at the International University Bremen in a core area supporting autonomy, i.e., mapping.     

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.     

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.     

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.     

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

Robotic urban search and rescue (USAR) is a challenging yet promising research area which has significant application potentials as has been seen during the rescue and recovery operations of recent disaster events. To date, the majority of rescue robots used in the field are teleoperated. In order to minimize a robot operator’s workload in time-critical disaster scenes, recent efforts have been made to equip these robots with some level of autonomy. This paper provides a detailed overview of developments in the exciting and challenging area of robotic control for USAR environments. In particular, we discuss the efforts that have been made in the literature towards: 1) developing low-level controllers for rescue robot autonomy in traversing uneven terrain and stairs, and perception-based simultaneous localization and mapping (SLAM) algorithms for developing 3D maps of USAR scenes, 2) task sharing of multiple tasks between operator and robot via semi-autonomous control, and 3) high-level control schemes that have been designed for multi-robot rescue teams.     

Distributed multirobot exploration, mapping, and task allocation

We present an integrated approach to multirobot exploration, mapping and searching suitable for large teams of robots operating in unknown areas lacking an existing supporting communications infrastructure. We present a set of algorithms that have been both implemented and experimentally verified on teams—of what we refer to as Centibots—consisting of as many as 100 robots. The results that we present involve search tasks that can be divided into a mapping stage in which robots must jointly explore a large unknown area with the goal of generating a consistent map from the fragment, a search stage in which robots are deployed within the environment in order to systematically search for an object of interest, and a protection phase in which robots are distributed to track any intruders in the search area. During the first stage, the robots actively seek to verify their relative locations in order to ensure consistency when combining data into shared maps; they must also coordinate their exploration strategies so as to maximize the efficiency of exploration. In the second and third stages, robots allocate search tasks among themselves; since tasks are not defined a priori, the robots first produce a topological graph of the area of interest and then generate a set of tasks that reflect spatial and communication constraints. Our system was evaluated under extremely realistic real-world conditions. An outside evaluation team found the system to be highly efficient and robust.     

Formation of a geometric pattern with a mobile wireless sensor network

Mobile wireless sensor networks (MWSNs) will enable information systems to gather detailed information about the environment on an unprecedented scale. These self‐organizing, distributed networks of sensors, processors, and actuators that are capable of movement have a broad range of potential applications, including military reconnaissance, surveillance, planetary exploration, and geophysical mapping. In many of the foreseen applications, the MWSN will need to form a geometric pattern without assistance from the user. In military reconnaissance, for example, the nodes will be dropped onto the battlefield from a plane and land at random positions. The nodes will be expected to arrange themselves into a predetermined formation in order to perform a specific task. Thus, we present algorithms for forming a line, circle, and regular polygon from a given set of random positions. The algorithms are distributed and use no communication between the nodes to minimize energy consumption. Unlike past studies of geometric problems where algorithms are either tested in simulations where each node has global knowledge of all the other nodes or implemented on a small number of robots, the robustness of our algorithms has been studied with simulations that model the sensor system in detail. The simulations demonstrate that the algorithms are robust against random errors in the sensors and actuators. © 2004 Wiley Periodicals, Inc.     

Tunnel passing maneuvers of prescribed formations

Tunnel passing is a pattern formation of multiple robots, an outcome of formation control which is the general problem of controlling a large number of robots required to move as a group. Tunnel passing deals with the task of driving a team of robots from arbitrary initial positions through a tunnel of given geometry. This paper proposes a decentralized planner that guarantees collision‐free tunnel passing maneuvers of a team of nonholonomic car‐like robots fixed in a prescribed formation, while considering all the practical limitations and constraints due to nonholonomy, tunnel geometry, and the formation specifications. Although solutions in literature are restricted to tunnels with linear segments, this paper introduces piecewise tunnel walls with straight and curved segments. The motion planner, derived from the Lyapunov‐based control scheme works within an overarching leader‐follower framework to generate either split/rejoin or expansion/contraction of the formation, as feasible solutions. Results from simulating virtual scenarios demonstrated the effectiveness of the proposed nonlinear controllers. Copyright © 2012 John Wiley & Sons, Ltd.     

LinesLab: A Flexible Low‐Cost Approach for the Generation of Physical Monochrome Art

The desire for the physical generation of computer art has seen a significant body of research that has resulted in sophisticated robots and painting machines, together with specialized algorithms mimicking particular artistic techniques. The resulting setups are often expensive and complex, making them unavailable for recreational and hobbyist use. In recent years, however, a new class of affordable low‐cost plotters and cutting machines has reached the market. In this paper, we present a novel system for the physical generation of line and cut‐out art based on digital images, targeted at such off‐the‐shelf devices. Our approach uses a meta‐optimization process to generate results that represent the tonal content of a digital image while conforming to the physical and mechanical constraints of home‐use devices. By flexibly combining basic sets of positional and shape encodings, we are able to recreate a wide range of artistic styles. Furthermore, our system optimizes the output in terms of visual perception based on the desired viewing distance, while remaining scalable with respect to the medium size.     

无线传感网络中的分簇算法综述

近年来无线传感网络的研究和应用取得了长足进展,其应用领域涵盖抢险救灾、战场侦察、资源保护、安全监控和智能家居等.为了改善传感网络的性能和提高可扩展性,节点往往按照分簇结构进行组织.本文介绍了分簇算法产生的背景和作用,说明了分簇算法需要考虑的因素、分簇目标、特性和复杂性.然后,基于收敛速率、簇结构稳定性和节能意识等方面概...     

Exploiting Spatial Locality and Heterogeneity of Agents for Search and Rescue Teamwork*

We propose coordination mechanisms for multiple heterogeneous physical agents that operate in city‐scale disaster scenarios, where they need to find and rescue people and extinguish fires. Large‐scale disasters are characterized by limited and unreliable communications; dangerous events that may disable agents; uncertainty about the location, duration, and type of tasks; and stringent temporal constraints on task completion times. In our approach, agents form teams with other agents that are in the same geographical area. Our algorithms either yield stable teams formed up front and never change, fluid teams where agents can change teams as need arises, or teams that restrict the types of agents that can belong to the same team. We compare our teaming algorithms against a baseline algorithm in which agents operate independently of others and two state‐of‐the‐art coordination mechanisms. Our algorithms are tested in city‐scale disaster simulations using the RoboCup Rescue simulator. Our experiments with different city maps show that, in general, forming teams leads to increased task completion and, specifically, that our teaming method that restricts the types of agents in a team outperforms the other methods.     

Robot and sensor networks for first responders

The need to collect, integrate, and communicate information effectively in emergency response scenarios exceeds the state of the art in information technology. This emergency response problem provides an interesting and important test bed for studying networks of distributed mobile robots and sensors. Here, we describe the component technologies required to deploy a networked-robot system that can augment human firefighters and first responders, significantly enhancing their firefighting capabilities. In a burning building at a firefighting training facility, we deployed a network of stationary Mote sensors, mobile robots with cameras, and stationary radio tags to test their ability to guide firefighters to targets and warn them of potential dangers. Our long-term vision is a physical network that can sense, move, compute, and reason, letting network users (firefighters and first responders) Google for physical information - that is, information about the location and properties of physical objects in the real world.     

改进的Dijkstra算法在灾害决策系统中的应用

灾害决策系统中,核心安置点的选择对救灾工作效率影响重大;分析常用的最短路径搜索方法,选用Dijkstra算法并对其进行改进,计算选取到达最远安置点最近的安置点作为核心安置点。实验结果表明,该方法具有良好的实用性。     

Bi‐objective stochastic programming models for determining depot locations in disaster relief operations

This paper presents two‐stage bi‐objective stochastic programming models for disaster relief operations. We consider a problem that occurs in the aftermath of a natural disaster: a transportation system for supplying disaster victims with relief goods must be established. We propose bi‐objective optimization models with a monetary objective and humanitarian objective. Uncertainty in the accessibility of the road network is modeled by a discrete set of scenarios. The key features of our model are the determination of locations for intermediate depots and acquisition of vehicles. Several model variants are considered. First, the operating budget can be fixed at the first stage for all possible scenarios or determined for each scenario at the second stage. Second, the assignment of vehicles to a depot can be either fixed or free. Third, we compare a heterogeneous vehicle fleet to a homogeneous fleet. We study the impact of the variants on the solutions. The set of Pareto‐optimal solutions is computed by applying the adaptive Epsilon‐constraint method. We solve the deterministic equivalents of the two‐stage stochastic programs using the MIP‐solver CPLEX.     

A Small and Lightweight Autonomous Laser Mapping System without GPS

Autonomous mapping systems execute multiple tasks that include navigation, location, and map generation via the collaborative work of multiple sensors. They are the object of a substantial research focus in the fields of robotics and remote sensing. Although the state‐of‐the‐art mobile mapping systems typically found in ready‐made vehicles or robots are reliable, they are rather large and heavy, their cost is high, and they generally use GPS and an inertial measurement unit to position, so their working environments are limited. After reviewing the current state of autonomous mapping systems, we describe the design and development of a small and lightweight autonomous mapping system (ASQ‐6DMapSys) without GPS, which incorporates low‐cost sensors and components. We describe the layout and selection strategy for sensors and other components in detail, and we present the design methodology for each subsystem. The ASQ‐6DMapSys employs a two‐dimensional (2D) lidar, an inclinometer, and two wheel encoders, which constitute a pose subsystem that uses extended Kalman filtering and simultaneous localization and mapping techniques to compute the pose of the vehicle body. A low‐cost 3D lidar that we developed is also installed on the vehicle body, and the resultant data are aligned with the corresponding pose data of the vehicle body to build a 3D point cloud that describes the global geometry of the environment. We designed and developed every subsystem of the ASQ‐6DMapSys, including the robot vehicle, so it will be easy to expand its functions in the future. The ASQ‐6DMapSys performs well in indoor, outdoor, and tunnel environments, and the experiments in different environments show that the ASQ‐6DMapSys is an effective, small, and lightweight autonomous mapping system with a high performance/price ratio.     

Prioritized Mobile Robot Exploration Based on Percolation Enhanced Entropy Based Fast SLAM

The major aim in search and rescue using mobile robots is to detect and reach trapped survivors and to support rescue operations through disaster environments. Our motivation is based on the fact that a search and rescue (SAR) robot can navigate within and penetrate a disaster area only if the area in question possesses connected voids. Traversability or penetrability of a disaster area is a primary factor that guides the navigation of a search and rescue (SAR) robot, since it is highly desirable that the robot, without hitting a dead end or getting stuck, keeps its mobility for its primary task of reconnaissance and mapping when searching the highly unstructured environment. We propose a novel percolation guidance that collaborates with entropy based SLAM under a switching control setting the priority to either position or map accuracy. This newly developed methodology has proven to combine the superiority of both percolator guidance and entropy based prioritization so that the active SLAM becomes speedy, with high coverage rate of the area as well as increased accuracy in localization. Our percolator guidance stems from a frontier based conditioning of a-posteriori occurrences of upcoming connected voids that uses the fact that every obstacle partially seen at the frontier of the explored domain has a spatial continuity into the unexplored area. The developed modular architecture is introduced in details and demonstrative examples are provided and discussed.     

Experimental Tests of ‘Bidi-bot’: A Mechanism Designed for Clearing Loose Debris from the Path of Mobile Search and Rescue Robots

Urban search and rescue robots have the potential of identifying the location of trapped people following a disaster. The majority of survivors in open spaces will be rapidly located and extracted by rescue personnel. Therefore, the greatest challenge for rescue robotics is to penetrate deep within collapsed buildings to search for survivors. In this paper, several robotic challenges are presented to represent some of the challenges faced within a collapsed building. A robotic mechanism, termed the sweep-extend mechanism is proposed as a means for mobile search and rescue robots to clear a path through loose debris. The mechanism has been mounted on a mobile platform and tested against the proposed scenarios. The mechanism was demonstrated to move debris, such as bricks, away from the path of the robot. The work also highlights limitations in the mechanism’s ability to deal with densely packed debris, collections of large debris, and the need for robust dust shielding.     

Monocular Vision for Long‐term Micro Aerial Vehicle State Estimation: A Compendium

The recent technological advances in Micro Aerial Vehicles (MAVs) have triggered great interest in the robotics community, as their deployability in missions of surveillance and reconnaissance has now become a realistic prospect. The state of the art, however, still lacks solutions that can work for a long duration in large, unknown, and GPS‐denied environments. Here, we present our visual pipeline and MAV state‐estimation framework, which uses feeds from a monocular camera and an Inertial Measurement Unit (IMU) to achieve real‐time and onboard autonomous flight in general and realistic scenarios. The challenge lies in dealing with the power and weight restrictions onboard a MAV while providing the robustness necessary in real and long‐term missions. This article provides a concise summary of our work on achieving the first onboard vision‐based power‐on‐and‐go system for autonomous MAV flights. We discuss our insights on the lessons learned throughout the different stages of this research, from the conception of the idea to the thorough theoretical analysis of the proposed framework and, finally, the real‐world implementation and deployment. Looking into the onboard estimation of monocular visual odometry, the sensor fusion strategy, the state estimation and self‐calibration of the system, and finally some implementation issues, the reader is guided through the different modules comprising our framework. The validity and power of this framework are illustrated via a comprehensive set of experiments in a large outdoor mission, demonstrating successful operation over flights of more than 360 m trajectory and 70 m altitude change. ¹