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Toward robotic sensor webs: Algorithms, systems, and experiments

Toward robotic sensor webs: Algorithms, systems, and experim...

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作者： Chung, Hoam Oh, Songhwai Shim, David Hyunchul Sastry, S. Shankar Department of Mechanical and Aerospace Engineering Monash University Clayton VIC. 3800 Australia Seoul National University Seoul 151-744 Korea Republic of Department of Aerospace Engineering Korea Advanced Institute of Science and Technology Daejon 305-701 Korea Republic of Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA 94720 United States

This paper presents recent advances in multiagent sensing and operation in dynamic environments. Technology trends point towards a fusion of wireless sensor networks with robotic swarms of mobile robots. In this paper, we discuss the coordination and collaboration between networked robotic systems, featuring algorithms for cooperative operations such as unmanned aerial vehicles (UAVs) swarming. We have developed cooperative actions of groups of agents such as probabilistic pursuit-evasion game for search and rescue operations, protection of resources, and security applications. We have demonstrated a hierarchical system architecture which provides wide-range sensing capabilities to unmanned vehicles through spatially deployed wireless sensor networks, highlighting the potential collaboration between wireless sensor networks and unmanned vehicles. This paper also includes a short review of our current research efforts in heterogeneous sensor networks, which is being evolved into mobile sensor networks with swarm mobility. In a very essential way, this represents the fusion of mobility of ensembles with the network embedded systems, the robotic sensor web. © 2011 IEEE.

关键词： Wireless sensor networks

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distributed robust data fusion based on dynamic voting

Distributed robust data fusion based on dynamic voting

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IEEE International conference on robotics and Automation (ICRA)

作者： Eduardo Montijano Sonia Martínez Carlos Sagues DIIS-13A University of Zaragoza Spain Department of Mechanical and AeroSpace Engineering University of California San Diego USA

Data association mistakes, estimation and measurement errors are some of the factors that can contribute to incorrect observations in robotic sensor networks. In order to act reliably, a robotic network must be able to fuse and correct its perception of the world by discarding any outlier information. This is a difficult task if the network is to be deployed remotely and the robots do not have access to ground-truth sites or manual calibration. In this paper, we present a novel, distributed scheme for robust data fusion in autonomous robotic networks. The proposed method adapts the RANSAC algorithm to exploit measurement redundancy, and enables robots determine an inlier observation with local communications. Different hypotheses are generated and voted for using a dynamic consensus algorithm. As the hypotheses are computed, the robots can change their opinion making the voting process dynamic. Assuming that at least one hypothesis is initialized with only inliers, we show that the method converges to the maximum likelihood of all the inlier observations in a general instance. Several simulations exhibit the good performance of the algorithm, which also gives acceptable results in situations where the conditions to guarantee convergence do not hold.

关键词： Robot kinematics Maximum likelihood estimation Robot sensing systems Convergence Robustness

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An itinerary for data fusion in distributed sensor network

An itinerary for data fusion in distributed sensor network

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IEEE International conference on Granular Computing (GRC)

作者： Meng Chen Xin Xia The Department of Computer NanChang University NanChang China JiangXi Vocational Technical College of Industry&Trade NanChang China

Using mobile agent for data fusion in distributed sensor network brings new problems, the serial itinerary of mobile agent travel makes long task duration, mobile agent transfer introduces new overhead, if a mission need collect data from all nodes many times mobile agent must be dispatched many times, which brings much data transfer overhead. To overcome these shortcomings, A closest first (CF) algorithm is presented to calculate a binary full spanning tree (BST) itinerary for mobile agent, full spanning tree ensuring shortest path. And the function of mobile agent is changed, when first reaching a node mobile agent give a copy of its code (called Resident Agent) into the node, resident agent can stay in the node for many times data collections and data fusion. Simulation shows that resident agent based data fusion can both reduce energy consumption and task duration time.

关键词： Mobile agents Energy consumption Data models Servers Algorithm design and analysis Computational modeling distributed databases

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distributed Mobility and Power Control for Noncooperative robotic Ad Hoc and sensor Networks

Distributed Mobility and Power Control for Noncooperative Ro...

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IEEE conference on Decision and Control

作者： Milos S. Stankovic Karl H. Johansson ACCESS Linnaeus Center School of Electrical Engineering KTH Royal Institute of Technology 100-44 Stockholm Sweden

ISBN: (纸本)9781612848006

In this paper we propose novel algorithms for noncooperative power and position control in mobile ad hoc networks. The algorithms are distributed and adaptive, i.e., they are able to deal with the agents' lack of knowledge about the environmental conditions and about the actions, positions and properties of the other agents, which is the essential challenge in these networks. The agents' cost functions consist of a term proportional to the achievable rate of communication with the neighbors, explicitly depending on the interference from the other agents, and a pricing term penalizing excessive power (for the power control scheme) or deviation from predefined positions (for the position control scheme). We formulate conditions for the existence and uniqueness of the Nash equilibrium and prove that the algorithms converge to it almost surely, based only on local measurements and local signaling between the neighbors. The position control algorithm can be adopted to specific motion dynamics of the networked mobile robots. We illustrate the main properties of the algorithms through simulations.

关键词： Power control Position control Nash equilibrium agents algorithms HALOGENATED ORGANIC COMPOUNDS Mobile ad hoc networks sensor networks ad hoc

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Multi-variate distributed Data fusion with Expensive sensor Data

Multi-variate Distributed Data Fusion with Expensive Sensor ...

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IEEE WIC ACM International conference on Web Intelligence (WI)

作者： Yonghong Wang Katia Sycara Paul Scerri Robotics Institute Carnegie Mellon University Pittsburgh PA USA

distributed fusion of complex information is critical to the success of large organizations. For such organizations, comprised of thousands of agents, improving and shaping the quality of conclusions reached is a challenging problem. The challenge is increased by the fact that acquisition of information could be costly. This leads to the crucial requirement that the organization should strive to reach correct conclusions while minimizing information acquisition cost. In this paper, we have developed a model of complex, interdependent information that is costly to acquire and where complex fusion should be optimized within an organization while minimizing the cost of acquiring the sensor data. Empirical results show a number of interesting effects. First, unselfish agents who spend resources (even when not strictly locally necessary) can lead to substantial improvement in the overall accuracy of the organization's conclusions. Second, an organization can substantially improve its performance by carefully assigning sensor resources within the organization. Third, over time, agents can learn the reliability of the members of the organization to whom they are directly connected to improve performance. Learning can also lead to better team decisions about whether to spend resources and how much resource to expend to get sensor data. Our conclusions and algorithms can help a range of organizations reach better conclusions while expending less resources procuring sensor data.

关键词： Organizations Robot sensing systems Reliability theory Data models Switches

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robotic test bed for autonomous surface exploration of Titan, Mars, and other planetary bodies

Robotic test bed for autonomous surface exploration of Titan...

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IEEE conference on Aerospace

作者： Wolfgang Fink Mark A. Tarbell Roberto Furfaro Linda Powers Jeffrey S. Kargel Victor R. Baker Jonathan Lunine Visual and Autonomous Exploration Systems Research Laboratory Division of Physics Mathematics and Astronomy California Institute of Technology Pasadena CA USA Visual and Autonomous Exploration Systems Research Laboratory Departments of Electrical & Computer Engineering Biomedical Engineering and Ophthalmology and Vision Science University of Arizona Tucson Tucson AZ USA Systems and Industrial Engineering Department University of Arizona Tucson Tucson AZ USA Department of Electrical & Computer Engineering University of Arizona Tucson Tucson AZ USA Department of Hydrology and Water Resources University of Arizona Tucson Tucson AZ USA Lunar and Planetary Laboratory University of Arizona Tucson Tucson AZ USA

Tier-scalable robotic reconnaissance missions are called for in extreme space environments, including planetary atmospheres, surfaces (both solid and liquid), and subsurfaces (e.g., oceans), as well as in potentially hazardous or inaccessible operational areas on Earth. Such future missions will require increasing degrees of operational autonomy: (1) Automatic mapping of an operational area from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and sensor data gathering; (3) automatic feature extraction and target/region-of-interest/anomaly identification within the mapped operational area; (4) automatic target prioritization for follow-up or close-up (in-situ) examination; and (5) subsequent automatic, targeted deployment and navigation/relocation of agents/sensors (e.g., to follow up on transient events). We report on recent progress in developing an Earth-based (outdoors) robotic test bed for Tier-scalable Reconnaissance at the University of Arizona and Caltech for distributed, science-driven, and significantly less constrained (compared to state-of-the-art) reconnaissance of prime locations on a variety of planetary bodies, with particular focus on Saturn's moon Titan with its methane/hydrocarbon lakes and Mars. The test bed currently comprises several computer-controlled robotic surface vehicles, i.e., rovers and lake landers/boats equipped with a variety of sensors. To achieve a fully operational Tier-scalable Reconnaissance test bed, aerial platforms will be integrated as a next step. The robotic surface vehicles can be interactively or automatically controlled from anywhere in the world in near real-time via the Internet. The test bed enables the implementation, field-testing, and validation of algorithms and strategies for navigation, exploration, sensor deployment, sensor data gathering, feature extraction, anomaly detection, and science goal prioritization for autonomous planetary exploration. Furthermor

关键词： Robot sensing systems Sea surface Cameras Reconnaissance Boats Lakes

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Deployment of an unreliable robotic sensor network for spatial estimation 49

Deployment of an unreliable robotic sensor network for spati...

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49th IEEE conference on Decision and Control (CDC)

作者： Cortes, Jorge Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92103 USA

ISBN: (纸本)9781424477463

This paper studies an optimal deployment problem for a network of robotic sensors moving in the real line. Consider the scenario where each sensor is to take a measurement of a spatial process of interest and send it back to a data fusion center. Assume only a specific fraction of the messages containing the measurements will arrive at the center. We show that, for several fraction values, the optimal deployment configurations have the following features: agents are grouped into clusters, the clusters are deployed optimally as if at least a message from each cluster was guaranteed to reach the center, and for each fraction value, there is a specific optimal cluster size. The technical approach combines convex analysis, nonsmooth analysis, and combinatorics.

关键词： sensor networks

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Intelligent processing research for target fusion recognition system based on multi-agents

Intelligent processing research for target fusion recognitio...

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International conference on Computational Intelligence and Software Engineering

作者： Wu, Xia Zhou, Yan Department of Early Warning and Surveillance Intelligence Air Force Radar Academy Wuhan China

ISBN: (纸本)9781424453924

According to the target fusion recognition under dynamic and uncertain target information conditions, a distributed target fusion recognition model is presented based on multi-agents. As a distributed multi-agents target recognition system, the model includes several widely distributed agent workgroups. The model is mainly made up of the detection agent, the recognition agent and the decision-making agent. The detection agent mainly realizes characteristics matching and sensor conditions controlling, the recognition agent is composed of information fusion algorithms into the nesting agents, the decision-making agent carries out various decision-making and cooperation mechanism. Then, the intelligent fusion processing under dynamic and uncertain environment is realized through communication and cooperation of the three agents for the actual condition request. It combines MAS and information fusion technology in target recognition system, and incarnates the advantages such as flexibility, reliability. Finally, by analyzing a ballistic target recognition experiment, the result is shown the model efficiency is advanced by the means. ©2010 IEEE.

关键词： Information fusion

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Spatial statistics and distributed estimation by robotic sensor networks

Spatial statistics and distributed estimation by robotic sen...

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作者： Graham, Rishi Cortés, Jorge Department of Applied Mathematics and Statistics University of California Santa Cruz United States Department of Mechanical and Aerospace Engineering University of California San Diego United States

ISBN: (纸本)9781424474264

Networks of environmental sensors are playing an increasingly important role in scientific studies of the ocean, rivers, and the atmosphere. robotic sensors can improve the efficiency of data collection, adapt to changes in the environment, and provide a robust response to individual failures. Their operation must be driven by statistically-aware algorithms that make the most of the network capabilities for data collection and fusion. At the same time, such algorithms need to be distributed and scalable to make robotic networks capable of operating in an autonomous and robust fashion. The combination of these two objectives, complex statistical modeling and distributed coordination, presents grand technical challenges: traditional statistical modeling and inference assume full availability of all measurements and central computation. While the availability of data at a central location is certainly a desirable property, the paradigm for distributed motion coordination builds on partial, fragmented information. This work surveys recent progress at bridging the gap between sophisticated statistical modeling and distributed motion coordination. © 2010 AACC.

关键词： Coordination reactions

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Multi sensor fusion Using Fitness Adaptive Differential Evolution

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1st International conference on Swarm, Evolutionary, and Memetic Computing

作者： Giri, Ritwik Ghosh, Arnob Chowdhury, Aritra Das, Swagatam Jadavpur Univ Dept Elect & Telecommun Engg Kolkata 700032 India

ISBN: (纸本)9783642175626

The rising popularity of multi-source, multi-sensor networks supports real-life applications calls for an efficient and intelligent approach to information fusion. Traditional optimization techniques often fail to meet the demands. The evolutionary approach provides a valuable alternative due to its inherent parallel nature and its ability to deal with difficult problems. We present a new evolutionary approach based on a modified version of Differential Evolution (DE), called Fitness Adaptive Differential Evolution (FiADE). FiADE treats sensors in the network as distributed intelligent agents with various degrees of autonomy. Existing approaches based on intelligent agents cannot completely answer the question of how their agents could coordinate their decisions in a complex environment. The proposed approach is formulated to produce good result for the problems that are high-dimensional, highly nonlinear, and random. The proposed approach gives better result in case of optimal allocation of sensors. The performance of the proposed approach is compared with an evolutionary algorithm coordination generalized particle model (C-GPM).

关键词： Multi-sensor fusion sensor behavior Evolutionary algorithm Dynamic sensor resource allocation problem Differential Evolution (DE)

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