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distributed Formation Estimation Via Pairwise Distance Measurements

IEEE roboticS AND AUTOMATION LETTERS 2021年第2期6卷 3017-3024页

作者： Ziegler, Thomas Karrer, Marco Schmuck, Patrik Chli, Margarita Swiss Fed Inst Technol Vis Robot Lab CH-8000 Zurich Switzerland

Continuously and reliably estimating the relative configuration of robotic swarms in real-time constitutes a core functionality when pursuing the autonomy of such a swarm. Relying on external positioning systems, such as GPS or motion tracking systems, can provide the required information, but significantly limits the generality of an approach. In this letter, we target formation estimation for autonomous flights of swarms of small UAVs, as they pose particularly challenging restrictions on onboard resources, while opening up a large variety of practical scenarios for a multi-robot setup. While state-of-the-art has been addressing efficient formation estimation, scalability remains limited to only very few agents that can be handled in real-time, with the workload of each agent depending on the total number of agents in the swarm. Aiming for scalable multi-robot systems, here we propose a distributed formation estimation approach, where the computational load of each agent is decoupled from the swarm size. This approach is implemented in a setup with minimal communication effort, requiring only ego-motion estimates from each agent and pairwise distance measurements between them, constraining their configuration globally. Evaluations on swarms of up to 49 UAVs demonstrate the power of our approach to handle large swarms, while keeping the computational load bounded for individual agents and requiring only little data exchange between two robots.

关键词： Robot sensing systems Estimation Unmanned aerial vehicles Scalability Location awareness Global Positioning System Collaboration Aerial systems multi-robot systems perception and autonomy sensor fusion

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Adaptive sampling using non-linear EKF with mobile robotic wireless sensor nodes

Adaptive sampling using non-linear EKF with mobile robotic w...

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9th International conference on Control, Automation, robotics and Vision

作者： Popa, D. O. Mysorewala, M. F. Lewis, F. L. Univ Texas Arlington Automat & Robot Res Inst Arlington TX 76019 USA

ISBN: (纸本)9781424403417

The use of robotics in distributed monitoring applications requires mobile wireless sensors that are deployed efficiently. Efficiency can be defined in multiple ways, such as in terms of the amount of energy expenditure, communication bandwidth or information content. A very important aspect of mobile sensor deployment includes sampling algorithms at location most likely to yield useful information about a field variable of interest. In this paper, we use inexpensive mobile robot nodes built in our lab (ARRI-Bots) as wireless sensor deployment agents, and we use them to demonstrate information efficient algorithms (e.g., "adaptive sampling"). Each mobile robot node is characterized by sensor measurement noise in addition to localization uncertainty. We use the Extended Kalman Filter (EKF) to derive quantitative information measures for sampling locations most likely to yield optimal information about the sampled field distribution. We present simulation and experimental results using this approach.

关键词： adaptive sampling sensor fusion kahnan filter field distribution monitoring

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A distributed Least-Squares Algorithm in Wireless sensor Networks with Limited Communication

A Distributed Least-Squares Algorithm in Wireless Sensor Net...

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IEEE International conference on Electro Information Technology (EIT)

作者： Wang, Jing Ahn, In Soo Lu, Yufeng Yang, Tianyu Staskevich, Gennady Bradley Univ Dept Elect & Comp Engn Peoria IL 61625 USA AFRL RISC Rome NY 13441 USA Embry Riddle Aeronaut Univ Dept Elect Comp Software & Syst Engn Daytona Beach FL 32114 USA

ISBN: (纸本)9781509047673

In this paper, a new distributed least-squares algorithm is proposed to solve the sensor fusion problem in using wireless sensor networks (WSN) to monitor the behaviors of large-scale multiagent systems. Under the assumption that each sensor can take the measurements of a limited number of agents but the complete multiagent systems are covered under the union of all sensors in the network, the proposed algorithm achieves the estimation consensus if local information exchange can be performed among sensors in sense of that the graph induced by communication topology is strongly connected. The convergence of the proposed algorithm is analyzed, and simulation results are provided to further illustrate its effectiveness.

关键词： Estimation Wireless sensor networks Multi-agent systems Topology Monitoring Eigenvalues and eigenfunctions sensor fusion

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distributed sampling of random fields with unknown covariance

Distributed sampling of random fields with unknown covarianc...

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American Control conference 2009

作者： Graham, Rishi Cortes, Jorge Univ Calif Santa Cruz Dept Appl Math & Stat Santa Cruz CA 95064 USA Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92093 USA

ISBN: (纸本)9781424445233

This paper considers robotic sensor networks performing spatial estimation tasks. We model a physical process of interest as a spatiotemporal random field with mean unknown and covariance known up to a scaling parameter. We design a distributed coordination algorithm for an heterogeneous network composed of mobile agents that take point measurements of the field and static nodes that fuse the information received from the agents and compute directions of maximum descent of the estimation uncertainty. The technical approach builds on a novel reformulation of Bayesian sequential field estimation, and combines tools from distributed linear iterations, nonlinear programming, and spatial statistics.

关键词： Mobile agents

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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： Montijano, Eduardo Martinez, Sonia Sagues, Carlos Univ Zaragoza DIIS I3A E-50009 Zaragoza Spain Univ Calif San Diego Dept Mech & Aerosp Engn La Jolla CA 92093 USA

ISBN: (纸本)9781612843858

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 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 whow 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： Mobile robotic Systems Robust Data fusion distributed Algorithms Dynamic Voting sensor Network Calibration

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Target assignment for robotic networks: Worst-case and stochastic performance in dense environments

Target assignment for robotic networks: Worst-case and stoch...

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46th IEEE conference on Decision and Control

作者： Smith, Stephen L. Bullo, Francesco Univ Calif Santa Barbara Ctr Control Dynam Syst & Computat Santa Barbara CA 93106 USA

ISBN: (纸本)9781424414970

Consider an equal number of mobile robotic agents and distinct target locations dispersed in an environment. Each agent has a limited communication range and knowledge of every target's position. We study the following target assignment problem: design a distributed algorithm with which the agents divide the targets among themselves and, simultaneously, move to their unique target. This paper focuses on "dense" environments, where the sum of the communication footprints is larger than the area of the environment. We introduce the class of monotonic algorithms, whose worst-case completion time is lower bounded by the area of the environment. We propose a monotonic algorithm called GRID ASSGMT and characterize its asymptotic performance: First, the algorithm is an asymptotically optimal monotonic algorithm for worst-case initial conditions. Second, for uniformly randomly distributed agents and targets the completion time is upper bounded by the diameter of the environment with high probability. Third, if the number of agents exceeds the number of targets by a logarithmic factor, then the completion time is constant with high probability. Our algorithm also solves a sensor based target assignment problem where agents have no initial knowledge of target positions, but acquire them via limited range sensing.

关键词： robotic arms

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Adaptive remote-sensing techniques implementing swarms of mobile agents

Adaptive remote-sensing techniques implementing swarms of mo...

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conference on Unattended Ground sensor Technologies and Applications

作者： Cameron, SM Loubriel, GM Robinett, RD Stantz, KM Trahan, MW Wagner, JS Sandia Natl Labs Albuquerque NM 87185 USA

ISBN: (纸本)0819431877

Measurement and signal intelligence (MASINT) of the battlespace has created new requirements in information management, communication and interoperability as they effect surveillance and situational awareness. In many situations, stand-off remote-sensing and hazard-interdiction techniques over realistic operational areas are often impractical and difficult to characterize. An alternative approach is to implement adaptive remote-sensing techniques with swarms of mobile agents employing collective behavior for optimization of mapping signatures and positional orientation (registration). We have expanded intelligent control theory using physics-based collective behavior models and genetic algorithms to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and inter-operative global optimization far sensor fusion and mission oversight. By using a layered hierarchical control architecture to orchestrate adaptive reconfiguration of semiautonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecking. In our concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelligence opens up a new class of remote sensing applications in which small single-function autonomous observers at the local level can collectively optimize and measure large scale ground-level signatures. As the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwi

关键词： emerging threats bio/chemical hazards ground-penetrating impulse radar laser vibrometry optical communications physics-based swarm model neural networks genetic algorithms

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distributed Detection and Isolation of sensor Faults in HVAC Systems

Distributed Detection and Isolation of Sensor Faults in HVAC...

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21st Mediterranean conference on Control and Automation (MED)

作者： Reppa, Vasso Papadopoulos, Panayiotis Polycarpou, Marios M. Panayiotou, Christos G. Univ Cyprus Dept Elect & Comp Engn KIOS Res Ctr Intelligent Syst & Networks CY-1678 Nicosia Cyprus

ISBN: (纸本)9781479909957;9781479909971

This paper presents the design of a methodology for distributed detection and isolation of multiple sensor faults in heating, ventilation and air-conditioning (HVAC) systems. The proposed methodology is developed in a distributed framework with the HVAC system modeled as a set of interconnected, nonlinear subsystems. A local sensor fault diagnosis (LSFD) agent is designed for each of the interconnected subsystems. The LSFD agent uses input and sensor output data of its underlying subsystem and it may exchange information with the neighboring agents. The distributed sensor fault detection is conducted using robust analytical redundancy relations, formulated by estimation-based residuals and adaptive thresholds. The distributed sensor fault isolation is carried out by combining the decisions of the LSFD agents and applying a reasoning-based decision logic. Simulation results are used for illustrating the effectiveness of the proposed methodology applied to a two-zone HVAC system.

关键词： HVAC fault diagnosis sensor fusion

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Analysis of distributed fusion alternatives in coordinated vision agents

Analysis of distributed fusion alternatives in coordinated v...

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11th International conference on Information fusion, fusion 2008

作者： Castanedo, Federico García, Jesús Patricio, Miguel A. Molina, José M. Applied Artificial Intelligence Group Computer Science Department University Carlos III of Madrid Spain

ISBN: (纸本)9783000248832

In this paper, we detail some technical alternatives when building a coherent distributed visual sensor network by using the Multi-Agent paradigm. We argue that the Multi-Agent paradigm fits well within the visual sensor network architecture and in this paper we specially focus on the problem of distributed data fusion. Three different data fusion coordination schemes are proposed and experimental results of Passive fusion are presented and discussed. The main contributions of this paper are twofold, first we propose the use of Multi-Agent paradigm as the visual sensor architecture and present a real system results. Secondly, the use of feedback information in the visual sensors, called Active fusion, is proposed. The experimental results prove that the Multi-Agent paradigm fits well within the visual sensor network and provide a novel mechanism to develop a real visual sensor network system.

关键词： Multi agent systems

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Towards optimal sensor morphology for specific tasks: Evolution of an artificial compound eye for estimating time to contact

Towards optimal sensor morphology for specific tasks: Evolut...

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conference on sensor fusion and Decentralized Control in robotic Systems III

作者： Lichtensteiger, L Univ Zurich Dept Comp Sci Artificial Intelligence Lab CH-8057 Zurich Switzerland

ISBN: (纸本)0819438618

For a systematic investigation of the interdependence between an agent's morphology and its task environment we constructed a system that is able to automatically generate optimal sensor morphologies for given tasks. The system consists of a robot with an artificial compound eye where the angular positions of the individual facets can be autonomously modified. This paper describes experiments on using artificial evolution to optimise the compound eye morphology for the task of estimating time to contact with obstacles. The resulting morphologies are in goad agreement with the theoretically predicted optimal sensor density distribution for this task. By comparing our results with earlier experiments we find that our robot is able to evolve different optimal morphologies depending on the task required. Since the accuracy of our system proved to be good enough to easily distinguish qualitatively different optimal sensor morphologies we hope that also for more complex task environments it will allow us to identify the optimal sensor distribution with good precision.

关键词： adaptive hardware morphology artificial compound eye artificial evolution autonomous agents

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