A flooding algorithm for multirobot exploration

In this paper, we present a multirobot exploration algorithm that aims at reducing the exploration time and to minimize the overall traverse distance of the robots by coordinating the movement of the robots performing the exploration. Modeling the environment as a tree, we consider a coordination model that restricts the number of robots allowed to traverse an edge and to enter a vertex during each step. This coordination is achieved in a decentralized manner by the robots using a set of active landmarks that are dropped by them at explored vertices. We mathematically analyze the algorithm on trees, obtaining its main properties and specifying its bounds on the exploration time. We also define three metrics of performance for multirobot algorithms. We simulate and compare the performance of this new algorithm with those of our multirobot depth first search (MR-DFS) approach presented in our recent paper and classic single-robot DFS.     

A generic multirobot control experimental system

This article describes a generic experimental system that implemented the activity controller theory. The controller has the ability to coordinate any number of robots (and other automated machines) and to respond to the random arrival of components, so as to efficiently assemble various mixes of products. The work also briefly presents the structure of the coordination system, and a solution frame to the dynamic collision avoidance problem. The computer-controlled experimental system is used to simultaneously operate two robots sharing tasks and auxiliary devices in an assembly cell.     

A spatial orthogonal allocation and heterogeneous cultural hybrid algorithm for multirobot exploration mission planning

A spatial orthogonal allocation method is devised for multirobot tasks allocation.A 3D space model is adopted to describe exploration mission;meanwhile spatial orthogonal tentative technology is utilized to update the attractor position for load balance.Heterogeneous interactive cultural hybrid architecture is proposed to solve a robot route planning problem;it utilizes good-point-set to initialize population spaces,redefine novel evolution model and particle evolution ability,and introduce near-neighbor lo...     

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.     

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.     

A novel 3D sensory system for robot-assisted mapping of cluttered urban search and rescue environments

In this paper, the first application of utilizing a unique 3D sensor for sequential 3D map building in unknown cluttered urban search and rescue (USAR) environments is proposed. The sensor utilizes a digital fringe projection and phase shifting technique to provide real-time 2D and 3D sensory information of the environment. The proposed sensor is unique over current technologies in that high-resolution 3D information of rubble filled environments can be acquired from the single sensor at a speed of 30 frames per second (fps). Furthermore, we propose the development of a novel robust and reliable landmark identification technique that utilizes both 2D and 3D depth images taken by the sensor for 3D mapping. Preliminary experiments show the potential of the real-time 3D sensory system and landmark identification scheme for robotic 3D mapping in unknown cluttered USAR-like environments.     

Morphology control in a multirobot system

In this article, we propose a distributed control mechanism for a self-propelled, self-assembling robotic system that allows robots to form specific, connected morphologies. Global morphologies are grown using only local visual perception. Robots that are part of the connected entity indicate where new robots should attach to grow the local structure appropriately. We demonstrate the efficacy of the mechanism by letting groups of seven real robots self-assemble into four different morphologies: line, star, arrow, and rectangle.     

A joint network for disaster recovery and search and rescue operations

Disasters are exceptional events that are either man made, such as terrorist attacks, or natural, such as earthquakes, wildfires and floods. Disasters create emergency situations and cause physical and social disorder. In these emergency situations, food, water, shelter, protection and medical help are needed, and the effort needed to provide these basic services to the victims must be coordinated quickly via a reliable communication network. A disaster recovery network is used to provide emergency support to both the disaster victims and the crewmembers that are helping the victims, and to provide a communication infrastructure in the disaster affected area. The disaster relief operation also involves searching for and locating the survivors, and then rescuing them. Currently this process involves manual search in the disaster area, which is also time consuming. A novel network architecture called the Portable Disaster Recovery Network is presented in this paper that enables survivors in a disaster area or a non-disaster related search-and-rescue situation to report their locations to a Command Center. This enables first responders to quickly rescue the survivors from these areas. This paper analyzes the performance of random walk models of the movement of survivors in the Portable Disaster Recovery Network.     

A hybrid approach for search and rescue using 3DCNN and PSO

Neural Computing and Applications - Search and rescue are essential applications of disaster management in which people are evacuated from the disaster-prone area to a safer place. This overall...     

CAMPOUT: a control architecture for tightly coupled coordination of multirobot systems for planetary surface exploration

Exploration of high risk terrain areas such as cliff faces and site construction operations by autonomous robotic systems on Mars requires a control architecture that is able to autonomously adapt to uncertainties in knowledge of the environment. We report on the development of a software/hardware framework for cooperating multiple robots performing such tightly coordinated tasks. This work builds on our earlier research into autonomous planetary rovers and robot arms. Here, we seek to closely coordinate the mobility and manipulation of multiple robots to perform examples of a cliff traverse for science data acquisition, and site construction operations including grasping, hoisting, and transport of extended objects such as large array sensors over natural, unpredictable terrain. In support of this work we have developed an enabling distributed control architecture called control architecture for multirobot planetary outposts (CAMPOUT) wherein integrated multirobot mobility and control mechanisms are derived as group compositions and coordination of more basic behaviors under a task-level multiagent planner. CAMPOUT includes the necessary group behaviors and communication mechanisms for coordinated/cooperative control of heterogeneous robotic platforms. In this paper, we describe CAMPOUT, and its application to ongoing physical experiments with multirobot systems at the Jet Propulsion Laboratory in Pasadena, CA, for exploration of cliff faces and deployment of extended payloads.     

A rescue robot designed for ease of use: development of exploration system using behavior of bombycid

Rescue operation is one of most effective applications of robots. However, previous rescue systems that use robots have a serious problem that is a shortage of professional operators. In this paper, we develop an exploration system of survivors using carbon dioxide, and to solve the problem we apply searching mechanism of bombycid to our system. To demonstrate the effectiveness of the proposed system, experiments have been conducted. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Remote sensing in sea search and rescue

A classified United States Army line scanner (Texas Instruments Model AAS-24) mounted in a Mohawk aircraft was tested for its air-sea search and rescue potential. Within the environmental parameters indicated the instrument proved effective in identifying both small boats and individual swimmers. Positive identification was made during daylight and night sorties when the location of swimmers was known and in daylight trials when their location was unknown.     

Developing search strategies for detecting relevant experiments

Our goal is to analyze the optimality of search strategies for use in systematic reviews of software engineering experiments. Studies retrieval is an important problem in any evidence-based discipline. This question has not been examined for evidence-based software engineering as yet. We have run several searches exercising different terms denoting experiments to evaluate their recall and precision. Based on our evaluation, we propose using a high recall strategy when there are plenty of resources or the results need to be exhaustive. For any other case, we propose optimal, or even acceptable, search strategies. As a secondary goal, we have analysed trends and weaknesses in terminology used in articles reporting software engineering experiments. We have found that it is impossible for a search strategy to retrieve 100% of the experiments of interest (as happens in other experimental disciplines), because of the shortage of reporting standards in the community.     

Generalized exploration in policy search

To learn control policies in unknown environments, learning agents need to explore by trying actions deemed suboptimal. In prior work, such exploration is performed by either perturbing the actions at each time-step independently, or by perturbing policy parameters over an entire episode. Since both of these strategies have certain advantages, a more balanced trade-off could be beneficial. We introduce a unifying view on step-based and episode-based exploration that allows for such balanced trade-offs. This trade-off strategy can be used with various reinforcement learning algorithms. In this paper, we study this generalized exploration strategy in a policy gradient method and in relative entropy policy search. We evaluate the exploration strategy on four dynamical systems and compare the results to the established step-based and episode-based exploration strategies. Our results show that a more balanced trade-off can yield faster learning and better final policies, and illustrate some of the effects that cause these performance differences.     

Database exploration in search of regularities

Large databases can be a source of useful knowledge. Yet this knowledge is implicit in the data. It must be mined and expressed in a concise, useful form of statistical patterns, equations, rules, conceptual hierarchies, and the like. Automation of knowledge discovery is important because databases are growing in size and number, and standard data analysis techniques are not designed for exploration of huge hypotheses spaces. We concentrate on discovery of regularities, defining a regularity by a pattern and the range in which that pattern holds. We argue that two types of patterns are particularly important: contingency tables and equations, and we present Forty-Niner (49er), a general-purpose database mining system which conducts large-scale search for those patterns in many subsets of data, conducting a more costly search for equations only when data indicate a functional relationship. 49er can refine the initial regularities to yield stronger and more general regularities and more useful concepts. 49er combines several searches, each contributing to a different aspect of a regularity. Correspondence between the components of search and the structure of regularities makes the system easy to understand, use, and expand. Finally, we discuss 49er's performance in four categories of tests: (1) open exploration of new databases; (2) reproduction of human findings (limited because databases which have been extensively explored are very rare); (3) hide- and -seek testing on artificially created data, to evaluate 49er on large scale against known results; (4) exploration of randomly generated databases.     

3D reconstruction of disaster scenes for urban search and rescue

Multimedia Tools and Applications - Natural and man-made disasters that may take place due to a catastrophic incident (e.g., earthquake, explosion, terrorist attack) often result in trapped humans...     

Development of rescue manipulator to search narrow space for victims

Recently, disasters such as earthquakes and so on occur at various places, and rescue operation using robots has attracted much attention. In this paper, we propose a new rescue robot with duplex mechanism that is realized by connecting two manipulators in parallel. We have demonstrated the validity and effectiveness of the proposed system by developing a prototype system. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008