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AIAA Guidance, Navigation and Control conference 2011

作者： Ponda, Sameera Ahmed, Nisar Luders, Brandon Sample, Eric Hoossainy, Tauhira Shah, Danelle Campbell, Mark How, Jonathan P. Dept. of Aeronautics and Astronautics MIT Cambridge MA United Kingdom Dept. of Mechanical and Aerospace Engineering Cornell University Ithaca NY United States

ISBN: (纸本)9781600869525

This paper introduces a novel planning and estimation framework for maximizing information collection in missions involving cooperative teams of multiple autonomous vehicles and human agents, such as those used for multi-target search and tracking. The main contribution of this work is the scalable unification of effective algorithms for distributed high-level task planning, decentralized information-based trajectory planning, and hybrid Bayesian information fusion through a common Gaussian mixture uncertainty representation, which can accommodate multiple mission objectives and constraints as well as heterogeneous human/robot information sources. The proposed framework is validated with promising results on real hardware through a set of experiments involving a human-robot team performing a multi-target search mission. © 2011 by Prof. Jonathan P. How, MIT, and Prof. Mark Campbell, Cornell University.

关键词： Robot programming

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Proceedings of the IEEE National Aerospace Electronics conference, NAECON

Proceedings of the IEEE National Aerospace Electronics Confe...

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2016 IEEE National Aerospace and Electronics conference and Ohio Innovation Summit, NAECON-OIS 2016

ISBN: (纸本)9781509034413

The proceedings contain 88 papers. The topics discussed include: a distributed, real-time simulation platform for aerospace power systems design, testing and evaluation;a novel adaptive technique for Li-ion battery model parameters estimation;target broker compression for multi-level fusion;face recognition based on modular histogram of oriented directional features;an ontology for active and passive aerial drone threat automatic plan recognition;using planar electrical impedance tomography as a structural health monitoring method to detect and evaluate the damage to CFRP composite;feature selection fusion (FSF) for aggregating relevance ranking information with application to ZigBee radio frequency device identification;error in parameter estimation in a multi-tier weak radio signal detection process with n simultaneous signals having continuous phase;secure, energy-efficient, interference-robust connectivity for physiological sensors using human body communication;automated design and optimization of integrated inductors and transformers;energy harvesting flexible regenerative power source for wearable devices;multi-spectral (optical/IR and RF) characterization of omnidirectional reflective dielectric thin film for sensor applications;pursuit-evasion game theoretic uncertainty oriented sensor management for elusive space objects;automated particle swarm optimization based PID tuning for control of robotic arm;development of advanced energy storage system using fuzzy control;and toward aircraft recognition with convolutional neural networks.

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Problems and solutions in acquisition and interpretation of sensorial data on a mobile robot

Conference Record - IEEE Instrumentation and Measurement Tec...

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conference Record - IEEE Instrumentation and Measurement Technology conference 1999年 2卷 831-836页

作者： Agazzi, Giovanni Bonarini, Andrea IDSIA Lugano Switzerland

We discuss some guidelines to cope with problems that arise when using cheap and simple sensor on mobile, autonomous, robotic agents. In particular we focus on the perceptual aliasing problem and on the possibility to perform active sensor data acquisition. We present a robotic architecture that we have implemented on a real robot following the proposed guidelines. The obtained mobile robot satisfies the design specifications, navigating autonomously in an unstructured environment.

关键词： sensor data fusion

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EKF-based Adaptive Sampling with Mobile robotic sensor Nodes

EKF-based Adaptive Sampling with Mobile Robotic Sensor Nodes

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2006 IEEE/RSJ International conference on Intelligent Robots and Systems

作者： D. O. Popa M. F. Mysorewala F. L. Lewis Automation & Robotics Research Institute (ARRI) University of Texas Arlington Fort Worth TX USA

The use of robotics in environmental monitoring applications requires distributed sensor systems optimized for effective estimation of relevant models subject to energy and environmental constraints. The mobile robot nodes are agents facilitating the repositioning of sensors in order to estimate a field distribution. This field distribution could be, for instance, water salinity in a lake, or air pollution over an industrial area. Each mobile robot node is characterized by sensor measurement noise in addition to localization uncertainty. This paper addresses an important problem for the robotic deployment of sensor networks, namely adaptive sampling (AS) by selection and repositioning of nodes in order to optimally estimate the parameters of distributed variable field models. The AS problem is posed as a sensor fusion problem within the extended Kalman filter (EKF) framework. We present simulation and experimental results of 2D deployment scenarios using low-cost mobile sensor robots developed in our lab

关键词： Sampling methods Mobile robots Robot sensing systems sensor phenomena and characterization Monitoring sensor systems Constraint optimization Water pollution Lakes Air pollution

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MAICS 2011 - Proceedings of the 22nd Midwest Artificial Intelligence and Cognitive Science conference 2011

MAICS 2011 - Proceedings of the 22nd Midwest Artificial Inte...

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22nd Midwest Artificial Intelligence and Cognitive Science conference 2011, MAICS 2011

The proceedings contain 34 papers. The topics discussed include: fuzzy relational visualization for decision support;a machine learning approach to identifying sections in legal briefs;automated speech act classification for online chat;a study of query-based dimensionality reduction;page ranking refinement using fuzzy sets and logic;computational intelligence for project scope;discovering causality in suicide notes using fuzzy cognitive maps;robotic dancing: exploring agents that use a stratified perceive-decide-act cycle of interaction;mining high quality association rules using genetic algorithms;support for agent based simulation of biomolecular systems;GEFeWS: a hybrid genetic-based feature weighting and selection algorithm for multi-biometric recognition;iris quality in an operational context;fusion of face and iris biometrics from a stand-off video sensor;and simplifying probability elicitation and uncertainty modeling in Bayesian networks.

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distributed expectation maximization in Appointment Rumor Routing in WSN

Distributed expectation maximization in Appointment Rumor Ro...

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2014 International conference on Information, Communication Technology and System, ICTS 2014

作者： Shokrzadeh, Hamid Bazyar, Nazanin Limanjoobi, Seyed Mohammad Yousefi Khorsandi, Siavash Roudehen Branch Islamic Azad University Young Researchers Club Roudehen Iran Qazvin Branch Islamic Azad University Qazvin Iran Lahijan Branch Islamic Azad University Lahjian Iran Dept. of Computer Eng. Amirkabir University of Technology Tehran Iran

ISBN: (纸本)9781479968572

One of the major problem in wireless sensor networks is query-driven routing, which especially arises when Sink searches for data for which the location in the network is unknown. Event information is propagated by Rumor Routing in some selected paths in the network, and as a result, an event trace is created. A route to the location of the event is established when a query agent crosses an event trace. The main objective of all Rumor-based algorithms is to increase the cross over rate for the query-agents. In Appointment-based Rumor Routing, contrary to other query-driven algorithms, agents' cross over occurs in a predetermined location called appointment point. In previous works, the appointment point is centrally calculated at the base station. In this paper, a distributed algorithm is proposed for appointment point selection. In order to estimate the parameters and the rank of a Gaussian Mixture used to model event locations, a distributed Expectation-Maximization algorithm is designed to estimate the rank and parameters. In this case, a data fusion algorithm as well as a novel approach called Active Gaussian Mean is employed to determine the appointment point. The results of simulation under multiple scenarios provide a comparison of the proposed algorithms with the ones in the literature. The results show that the proposed algorithms are nearly optimal. © 2014 IEEE.

关键词： Location

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Robot/UAV Indoor Visual SLAM in Smart Cities Based on Remote Data Processing

Robot/UAV Indoor Visual SLAM in Smart Cities Based on Remote...

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2023 International Russian Smart Industry conference, SmartIndustryCon 2023

作者： Jharko, Elena Mamchenko, Mark Khripunov, Sergey P. V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Laboratory of Distributed Information and Control Systems Moscow Russia V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Laboratory of Cyber-Physical Systems Moscow Russia

ISBN: (纸本)9781665464291

Indoor navigation is a topical issue in the use of robotics and unmanned aerial vehicles (UAVs) in a smart city, especially in the absence/weak signals of satellite navigation. One of the promising solutions of these issues is the use of visual simultaneous localization and mapping (vSLAM) algorithms, and one or more remote data processing servers for localization and map construction of the robots and the UAVs. The paper analyzes the current state of remote vSLAM and gives the requirements of a promising similar framework for UAVs in a smart city. In general, it is possible to distinguish two approaches to remote vSLAM systems for robots/UAVs. The first one implies sending raw data from sensors (video stream) via wireless connection directly to a remote server, which can be used for cloud/fog/edge computing. The second approach involves data pre-processing on the robots/UAVs, with subsequent transmission of data to the remote cloud/fog/edge computing server for further processing, acquiring map keyframes and map updates. The considered approaches, algorithms and solutions are classified by the type and the number of servers used, the maximum number of robotic agents/UAVs, the presence of navigation data fusion, as well as the type of video sensor used. Based on the analysis of existing solutions and vSLAM classification, it is possible to form a set of requirements for promising vSLAM systems for indoor navigation of robots/UAVs, including their camera input, resolution, number of frames per second (FPS), bandwidth, support of wireless standards, channels, and protocols, multi-robot/multi-server support, and time consumption. © 2023 IEEE.

关键词： Robots

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14th International conference on Informatics in Control, Automation and robotics, ICINCO 2017

14th International Conference on Informatics in Control, Aut...

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14th International conference on Informatics in Control, Automation and robotics, ICINCO 2017

ISBN: (纸本)9783030112912

The proceedings contain 39 papers. The special focus in this conference is on Informatics in Control, Automation and robotics. The topics include: Application of a distributed containment algorithm: Trajectory tracking forâ mobile robots;Stochastic DP based on trained database for sub-optimal energy management of hybrid electric vehicles;modelling and minimum cost control of multiple tank pumping systems;reliable on-line re-optimization control of a fed-batch fermentation process using bootstrap aggregated extreme learning machine;optimization algorithm for an exoskeleten robotic inverse kinematic application;a state dependent approach to resource allocation strategies;Auto-tuning of PID controllers for robotic manipulators using PSO and MOPSO;ATLASCAR: A sample of the quests and concerns for autonomous cars;intelligent labware transportation solution for the hierarchical life science automation;finite-Horizon H∞ Control Problem with Singular Control Cost;object detection and 6D pose estimation for precise robotic manipulation in unstructured environments;comprising of elastostatic and elastodynamic modeling for compliance error compensation in bipedal robot;autonomous navigation with open software platform for field robots;a multicopter design software tool for automated generation of simulation and visualization models;combining voronoi graph and spline-based approaches for a mobile robot path planning;geometrically finding best grasping points on single novel 3D point cloud;3D lidar data segmentation using a sequential hybrid method;ARTag, AprilTag and CALTag fiducial systems comparison in a presence of partial rotation: Manual and automated approaches;a simplified method to determine gravity vector through aerodynamic coefficients and its applications in attitude determination;sensor fusion approach for an autonomous shunting locomotive.

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Collaborative multi-modality target classification in distributed sensor networks

Collaborative multi-modality target classification in distri...

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International conference on Information fusion

作者： Xiaoling Wang Hairong Qi S.S. Iyengar Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA Department of Computer Science Louisiana State University Baton Rouge LA USA

ISBN: (纸本)0972184414

A new computing paradigm which utilizes mobile agents to carry out collaborative target classification in distributed sensor networks is presented in this paper. Instead of each sensor sending local classification results to a processing center where the fusion process is taken place, a mobile agent is dispatched from the processing center and the fusion process is executed at each sensor node. The advantage of using mobile agent is that it achieves progressive accuracy and is task-adaptive. To improve the accuracy of classification, we implement Behavior Knowledge Space method for multi-modality fusion. We also modified the classical k-nearest-neighbor method to be adaptive to collaborative classification in a distributed network of sensor nodes. Experimental results based on a field demo are presented at the end of the paper.

关键词： Collaboration Intelligent networks Multimodal sensors sensor fusion sensor phenomena and characterization Mobile agents Costs Wireless sensor networks Computer networks distributed computing

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Multi-object tracking with distributed sensing

Multi-object tracking with distributed sensing

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International conference on Multisensor fusion and Integration for Intelligent Systems (MFI)

作者： Ricardo Dias Nuno Lau Joao Silva Gi Hyun Lim DETI/IEETA University of Aveiro Aveiro Portugal

ISBN: (纸本)9781467397087;9781467397094

One of the main research goals on distributed autonomous agents in a Multi-Agent System is the development of mechanisms to form a better world model using information merging from different agents. In this paper, we present a solution for robust online and real-time multiple object tracking in a multi-agent system using information gathered by various agents over time, using COP-KMeans for clustering and Kalman Filtering for object state estimation. The proposed solution was implemented on a real robotic soccer team and evaluated in the RoboCup Middle-Size League competitions. The robotic soccer was presented as one possible application for the ideas expressed on this paper.

关键词： Robot sensing systems Robot kinematics Kalman filters Multi-agent systems Merging Object tracking

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