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检索条件"任意字段=Conference on Sensor Fusion and Distributed Robotic Agents"

共 371 条记录，以下是141-150 订阅

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A Multi-objective Optimization Approach for Data fusion in Mobile Agent Based distributed sensor Networks

A Multi-objective Optimization Approach for Data Fusion in M...

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International Instrumentation and Measurement Technology conference (I2MTC)

作者： Rajagopalan, Ramesh Univ St Thomas Sch Engn St Paul MN 55105 USA

ISBN: (纸本)9781424428335

A recent approach for data fusion in wireless sensor networks involves the use of mobile agents that selectively visit the sensors and incrementally fuse the data, thereby eliminating the unnecessary transmission of irrelevant or non-critical data. The order of sensors visited along the route determines the quality of the fused data and the communication cost. The computation of mobile agent routes involves tradeoffs between energy consumption, path loss, and detection accuracy. For instance, as the number of sensors in the route increases, the quality of fused data improves but the energy consumption and path loss increase. This paper models the mobile agent routing problem as a multi-objective optimization problem, maximizing the total detected signal energy while minimizing the energy consumption and path loss. A recently developed multi-objective evolutionary algorithm called the evolutionary multi-objective crowding algorithm (EMOCA) is employed for obtaining the mobile agent routes. The performance of EMOCA is compared with a recently proposed combinatorial optimization approach. Simulation results show that EMOCA outperforms the combinatorial optimization approach for different network sizes clearly demonstrating the advantage of a multi-objective optimization approach.

关键词： sensor networks data fusion mobile agent optimization

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"Data-centric to the max", the SPLICE architecture experience 23

"Data-centric to the max", the SPLICE architecture experienc...

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23rd International conference on distributed Computing Systems Workshops

作者： van 't Hag, JH Thales Naval Nederland Netherlands

ISBN: (纸本)0769519210

Over the past 10 years, Thales Naval Nederland (TNN) has successfully applied a pure data-centric architecture called SPLICE in its naval Combat Management Systems This fielded architecture provides the essential non-functional properties as demanded in these mission-critical environments such as (real-time) performance, scalability, fault-tolerance and evolve-ability. Thales recently contributed this knowledge and experience in a joint submission regarding the OMG's Data Distribution Service (DDS) for Real-time systems. The SPLICE architecture is characterized by autonomous applications with minimal dependencies where function and interaction are clearly separated and SPLICE-agents act as real-time information brokers. SPLICE thus offers a normalized environment that is designed once for all applications and which delivers 'the right information at the right place at the right time'.

关键词： Control systems distributed computing Environmental management Fault tolerant systems Mission critical systems Real time systems Scalability sensor fusion sensor systems Subscriptions

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Geometry-Aware distributed Kalman Filtering for Affine Formation Control under Observation Losses 26

Geometry-Aware Distributed Kalman Filtering for Affine Forma...

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26th International conference on Information fusion, fusion 2023

作者： Li, Zhonggang Rajan, Raj Thilak Delft University of Technology Signal Processing Systems Faculty of Eemcs Delft Netherlands

ISBN: (纸本)9798890344854

Affine formation control of multiagent systems has recently received increasing attention in various applications. The distributed control of these agents, under single integrator dynamics, relies on the observations of relative positions of the neighboring agents, which when unavailable is detrimental to the mission. In this paper, we propose an adaptive fusion estimator of the relative positions under intermittent and consecutive observation loss settings. A relative affine localization (RAL) solution is developed by exploiting the geometry of affine formation, which is then embedded into a distributed relative Kalman filtering (RKF) framework, leading to the geometry-aware relative Kalman filter (GA-RKF). We show through simulations that the GA-RKF exhibits enhanced robustness to both intermittent and consecutive observation losses, as compared to RAL and existing state-of-art methods. © 2023 International Society of Information fusion.

关键词： Multi agent systems

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Pose-graph Based 3D Map fusion with distributed Robot System

Pose-graph Based 3D Map Fusion with Distributed Robot System

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2014 IEEE International conference on robotics and Biomimetics (ROBIO)

作者： Chen, Haoyao Zhong, Jin Fu, Yanling Lou, Yunjiang Harbin Inst Technol Dept Mech Engn & Automat Shenzhen Peoples R China Harbin Inst Technol Shenzhen Grad Sch Shenzhen Key Lab Adv Control & Automat Shenzhen Peoples R China

ISBN: (纸本)9781479973972

Map fusion is an essential and challenging issue in multi-robot simultaneous localization and mapping (SLAM), especially for 3D SLAM applications. In this paper, we propose an efficient pose-graph based approach to fuse several 3D maps built by distributed mobile robotic system. Several robots, each equipped with a Kinect sensor, cooperate to map the operated environment;each of them just scans a part of the environment. A target detection algorithm is presented to help the robot detect other robots during the map building. Key information will be transferred from the detected robot to the detecting robot to build a link between these two robots. And at last, G20 optimization library is applied on the connected pose-graphs to build an optimized map. Experiments are finally performed to demonstrate the effectiveness of the proposed approach.

关键词： Graphic methods

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Hierarchical environment model for fusing information from human operators and robots

Hierarchical environment model for fusing information from h...

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IEEE/RSJ International conference on Intelligent Robots and Systems

作者： Kaupp, Tobias Douillard, Bertrand Upcroft, Ben Makarenko, Alexei Univ Sydney ARC Ctr Excellence Autonomous Syst CAS Sydney NSW 2006 Australia

ISBN: (纸本)9781424402588

This paper considers the problem of building environment models by fusing information gathered by robotic platforms with human perceptual information. Rich environment models are required in real applications for both autonomous operation of robots and to support human decision-making. Hierarchical models are well suited to represent complex environments because they: offer multiple abstractions of the available information to support analysis and decision-making, and permit the incorporation of higher-level human observations. The contributions of this paper are two-fold: (1) development of a probabilistic three-level environment model for distributed information gathering, and (2) experimental demonstration of fully decentralized, cooperative human-robot information gathering using an outdoor sensor network comprised of an unmanned air vehicle, a ground vehicle, and two human operators. Several information exchange patterns are presented which qualitatively demonstrate human-robot information fusion.

关键词： information fusion human-robot teams hierarchical model sensor network

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A distributed Multi-Robot Approach for the Detection and Tracking of Multiple Dynamic Anomalies

A Distributed Multi-Robot Approach for the Detection and Tra...

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IEEE International conference on robotics and Automation (ICRA)

作者： Saldana, David Assuncao, Renato Campos, Mario F. M. Univ Fed Minas Gerais Dept Comp Sci Comp Vis & Robot Lab VeRLab Belo Horizonte MG Brazil

ISBN: (纸本)9781479969234

In many cases, large area disasters could be possibly be prevented if the incipient small-scale anomalies are detected in their early stages. A way to accomplish this would be to have multiple sensors deployed in disaster prone areas to detect anomalies. However, compared to static sensor networks, robotic sensor networks offer advantages such as active sensing, large area coverage and anomaly tracking. This paper addresses the problem of coordinating and controlling multiple robots for the detection of multiple dynamic anomalies in the environment. The main contribution of the work is a combined approach for the effective exploration under uncertainty, the anomaly tracking, and the autonomous on-line allocation of agents. Robots explore the work area maintaining the history of the sensed areas to reduce redundancy and to allow for full-map coverage. When an anomaly is detected, a robot autonomously determines how to either track the anomaly or to continue the exploration of the environment, depending on the size of the anomaly, which is estimated by the length of the perimeter of the enclosing polygon. We show results of our methodology both in simulation and with actual robots which have demonstrated that robots can autonomously and distributively be allocated to track or to explore depending on the behavior of the detected anomalies.

关键词： Multi-robot systems robotic sensor networks particle filter perimeter detection tracking

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A holistic cloud-enabled robotics system for real-time video tracking application

A holistic cloud-enabled robotics system for real-time video...

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8th FTRA International conference on Future Information Technology, FutureTech 2013

作者： Liu, Bingwei Chen, Yu Blasch, Erik Pham, Khanh Shen, Dan Chen, Genshe Department of Electrical and Computer Engineering Binghamton University SUNY Binghamton NY United States Air Force Research Laboratory Rome NY United States Air Force Research Laboratory Kirtland AFB Albuquerque NM United States Intelligent Fusion Technology Inc. Germantown MD United States

ISBN: (纸本)9783642408601

Future distributed sensor fusion applications will require efficient methods of information management such as Cloud computing. Using a server-based cloud-enabled software architecture would increase performance over hardware constraints (e.g., power, memory, and processors). In this paper, we propose a comprehensive framework for information fusion demonstrated for Cloud robotics, which possesses user favorable features such as good scalability and elasticity. Robots are connected together to form a networked robotic system that is able to accomplish more computationally intensive tasks. Supported by the emerging Cloud computing technology, cloud-enabled robotic systems (CERS) provide even more powerful capabilities to users, yet keeping the simplicity of a set of distributed robots. Through an experimental study, we evaluate the memory, speed, and processors needed for a video tracking application. © 2014 Springer-Verlag.

关键词： Cloud computing

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Layered mode selection logic control with fuzzy sensor fusion network

Layered mode selection logic control with fuzzy sensor fusio...

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conference on Unmanned Systems Technology IX

作者： Born, Traig Wright, Andrew Hendrix Coll Dept Phys 1600 Washington Ave Conway AR 72032 USA Univ Arkansas Dept Appl Sci Little Rock AR 72204 USA

ISBN: (纸本)9780819466839

Robots developed from the 60's to the present have been restricted to highly structured environments such as work cells or automated guided vehicles, primarily to avoid harmful interactions with humans. Next generation robots must function in unstructured environments. Such robots must be fault tolerant to sensor and manipulator failures, scalable in number of agents, and adaptable to different robotic base platforms. The Central Arkansas robotics Consortium has developed a robot controller architecture, called Layered Mode Selection Logic (LMSL), which addresses all of these concerns. The LMSL architecture is an implementation of a behavior based controller fused with a planner. The architecture creates an abstraction layer for the robot sensors through a Fuzzy sensor fusion Network (FSFN), and it creates an abstraction layer for the robot manipulators through a reactive layer. The LMSL architecture has been implemented and tested on UALR's J5 robotics research platform. A FSFN combines acceleration and force signals for collision detection. The output of the FSFN switches among low level behaviors to accomplish obstacle avoidance and obstacle manipulation. Comparable results are achieved with all sensors functioning, with only the acceleration sensor (force sensor faulted), and with only the force sensor (acceleration sensor faulted).

关键词： mode selection logic fuzzy logic sensor fusion fault tolerance

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distributed multi-agent magnetic field norm SLAM with Gaussian processes 26

Distributed multi-agent magnetic field norm SLAM with Gaussi...

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26th International conference on Information fusion, fusion 2023

作者： Viset, Frida Helmons, Rudy Kok, Manon Delft University of Technology Delft Center for Systems and Control Netherlands Delft University of Technology Norwegian University of Science and Technology Maritime and Transport Technology Institute for Geoscience and Petroleum Norway

ISBN: (纸本)9798890344854

Accurately estimating the positions of multi-agent systems in indoor environments is challenging due to the lack of Global Navigation Satelite System (GNSS) signals. Noisy measurements of position and orientation can cause the integrated position estimate to drift without bound. Previous research has proposed using magnetic field simultaneous localization and mapping (SLAM) to compensate for position drift in a single agent. Here, we propose two novel algorithms that allow multiple agents to apply magnetic field SLAM using their own and other agents' *** first algorithm is a centralized approach that uses all measurements collected by all agents in a single extended Kalman filter. This algorithm simultaneously estimates the agents' position and orientation and the magnetic field norm in a central unit that can communicate with all agents at all times. In cases where a central unit is not available, and there are communication drop-outs between agents, our second algorithm is a distributed approach that can be *** tested both algorithms by estimating the position of magnetometers carried by three people in an optical motion capture lab with simulated odometry and simulated communication dropouts between agents. We show that both algorithms are able to compensate for drift in a case where single-agent SLAM is not. We also discuss the conditions for the estimate from our distributed algorithm to converge to the estimate from the centralized algorithm, both theoretically and experimentally. Our experiments show that, for a communication drop-out rate of 80%, our proposed distributed algorithm, on average, provides a more accurate position estimate than single-agent SLAM. Finally, we demonstrate the drift-compensating abilities of our centralized algorithm on a real-life pedestrian localization problem with multiple agents moving inside a building. © 2023 International Society of Information fusion.

关键词： Magnetic fields

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Robust Visual Simultaneous Localization and Mapping for MAV Using Smooth Variable Structure Filter 2nd

Robust Visual Simultaneous Localization and Mapping for MAV ...

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2nd Iberian robotics conference (ROBOT)

作者： Nemra, Abdelkrim Bergasa, Luis M. Lopez, Elena Barea, Rafael Gomez, Alejandro Saltos, Alvaro Ecole Mil Polytech Algiers Algeria Alcala Univ Dept Elect Alcala De Henares Spain

ISBN: (纸本)9783319271460;9783319271453

The work presented in this paper is a part of research work on autonomous navigation for Micro Aerial Vehicles (MAVs). Simultaneous Localization and Mapping (SLAM) is crucial for any task of MAV navigation. The limited payload of the MAV makes the single camera as best solution for SLAM problem. In this paper the Large Scale Dense SLAM (LSD-SLAM) pose is fused with inertial data using Smooth Variable Structure Filter which is a robust filter. Our MAV-SVSF-SLAM application is developed under Linux using robotic Operating System (ROS) so that the code can be distributed in different nodes, to be used in other applications of guidance, control and navigation. The proposed approach is validated first in simulation, then experimentally using the Bebop Quadrotor in indoor and outdoor environment and good results have been obtained.

关键词： Micro Aerial Vehicles Simultaneous Localization and Mapping Autonomous navigation Data fusion Robust filters sensor fusion robotic Operating System

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