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Conference on sensor fusion and decentralized control in Autonomous robotic systems

作者： Nashman, M Yoshimi, B Hong, TH Rippey, WG Herman, M National Institute of Standards and Technology Bldg. 220B124 Gaithersburg MD 20899 United States

ISBN: (纸本)0819426415

This paper describes a real-time hierarchical system that fuses data from vision and touch sensors to improve the performance of a coordinate measuring machine (CMM) used for dimensional inspection tasks. The system consists of sensory processing, world modeling, and task decomposition modules. It uses the strengths of each sensor-the precision of the CMM scales and the analog touch probe and the global information provided by the low resolution camera-to improve the speed and flexibility of the inspection task. In the experiment described, the vision module performs all computations in image coordinate space. The part's boundaries' are extracted during an initialization process and then the probe's position is continuously updated as it scans and measures the part surface. The system fuses the estimated probe velocity and distance to the part boundary in image coordinates with the estimated velocity and probe position provided by the CMM controller. The fused information provides feedback to the motion controller as it guides the touch probe to scan the part. We also discuss integrating information from the vision system and the probe to autonomously collect data for 2-D to 3-D calibration, and work to register Computer Aided Design (CAD) models with images of parts in the workplace.

关键词： computer aided design (CAD) calibration computer vision coordinate measuring machine (CMM) real-time control system (RCS) sensor fusion touch probe

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Model-based control of glass melting furnaces and forehearths: First principles-based model of predictive control system design

Model-based control of glass melting furnaces and forehearth...

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sensor fusion and decentralized control in robotic systems iv

作者： Backx, Ton C. Huisman, Leo Astrid, Patricia Beerkens, Ruud IPCOS Technology Boxtel Netherlands Eindhoven University of Technology Eindhoven Netherlands

An overview is given of new developments in the area of process modeling for model-based control system design. Focus is on the state of the art in model predictive control. Results obtained by applying these techniqu... 详细信息

关键词： Melting furnaces

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Grid-based framework for sensorial data integration in mobile robots

Grid-based framework for sensorial data integration in mobil...

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Conference on sensor fusion and decentralized control in Autonomous robotic systems

作者： Silva, A Menezes, P Dias, J Araujo, H Univ. de Coimbra (Portugal)

ISBN: (纸本)0819426415

This article presents a method to combine data from two sensorial modalities, a stereoscopic vision based sensor and a ring of ultrasonic sensors, in a grid based framework for obstacle detection and avoidance with mobile robots. The sensors' data is combined using Dempster-Shafer theory. This theory allows the combination of multiple sensorial data sources in a way that they are mutually enhanced and validated. A connectionist grid is used to support these operations and the environment modeling. Each grid node maps a configuration in a discrete subset of the robot's configuration space. The process used to obtain obstacle presence information from the stereoscopic setup and ultrasonic sensors is explained in detail. Detected obstacles result in sets of restricted configurations. The grid dynamic behavior allows the iterative computation of a repulsive potential field, which rises in the vicinity of the restricted configurations. As new information is collected by the sensors during the robot's motion so new configurations are marked as restrict and the potential field changes accordingly. Since this process occurs in real time, the computed potential field can he used to navigate the robot avoiding the detected obstacles. Experimental results are presented to support the used sensor models, the integration procedure and the control strategy.

关键词： obstacle detection sensor fusion mobile robot navigation

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Data fusion for 3D object reconstruction

Data fusion for 3D object reconstruction

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Mostafa, MGH Yamany, SM Farag, AA Univ Louisville EE Dept Comp Vis & Image Proc Lab Louisville KY 40292 USA

ISBN: (纸本)0819429848

Recently multisensor data fusion has proven its necessity for computer vision and robotics applications. Three-dimensional (3D) scene reconstruction and model building have been greatly improved in systems that employ multiple sensors and/or multiple cues data fusion/integration. In this paper, we present a framework for integrating registered multiple sensory data, sparse range data from laser range finders and dense depth maps of shape from shading from intensity images, for improving the 3D reconstruction of visible surfaces of 3D objects. Two methods are used for data integration and surface reconstruction. In the first method, data are integrated using a local error propagation algorithm, which we have developed in this paper. In the second method, the integration process is carried out using a feedforward neural networks with backpropagation learning rule. It is found that the integration of sparse depth measurements has greatly enhanced the 3D visible surface obtained from shape from shading in terms of metric measurements. We also review the current research in the area of multisensor/multicue data fusion for 3D object reconstructions.

关键词： data fusion computer vision surface reconstruction surface interpolations shape from shading neural networks

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Decision and feature fusion over the fractal inference network using camera and range sensors

Decision and feature fusion over the fractal inference netwo...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Erkmen, I Erkmen, AM Ucar, E Middle E Tech Univ Dept Elect & Elect Engn TR-06531 Ankara Turkey

ISBN: (纸本)0819429848

The objective of the ongoing work is to fuse information from uncertain environmental data taken by cameras, short range sensors including infrared and ultrasound sensors for strategic target recognition and task specific action in Mobile Robot applications. Our present goal in this paper is to demonstrate target recognition for service robot in a simple office environment. It is proposed to fuse all sensory signals obtained from multiple sensors over a fully layer-connected sensor network system that provides an equal opportunity competitive environment for sensory data where those bearing less uncertainty, less complexity and less inconsistencies with the overall goal survive, while others fade out. In our work, this task is achieved as a decision fusion using the Fractal Inference Network (FIN), where information patterns or units- modelled as textured belief functions bearing a fractal dimension due to uncertainty - propagate while being processed at the nodes of the network. Each local process of a node generates a multiresolutional feature fusion. In this model, the environment is observed by multisensors of different type, different resolution and different spatial location without a prescheduled sensing scenario in data gathering. Node activation and flow control of information over the FIN is performed by a neuro-controller, a concept that has been developed recently as an improvement over the classical Fractal Inference Network. In this paper, the mathematical closed form representation for decision fusion over the FIN is developed in a way suitable for analysis and is applied to a NOMAD mobile robot servicing an office environment.

关键词： fractal inference network multiresolutional sensor fusion belief functions evidential logical sensors textured belief networks

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Fault tolerant action selection for planetary rover control

Fault tolerant action selection for planetary rover control

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Huntsberger, T Univ S Carolina Dept Comp Sci Intelligent Syst Lab Columbia SC 29208 USA

ISBN: (纸本)0819429848

The ability of a small rover to operate semi-autonomously in a hazardous planetary environment was recently demonstrated by the Sojourner mission to Mars in July of 1997. Sojourner stayed within a 50 meter radius of the Pathfinder lander. Current NASA plans call for extended year-long multikilometer treks for the 2003 and 2005 missions. A greater deal of rover autonomy is required for such missions. We have recently developed a hybrid wavelet/neural network based system called BISMARC (Biologically Inspired System for Map-based Autonomous Rover control), that is capable of such autonomy. Simulations reported at this meeting last year demonstrated that the system is capable of control for multiple rovers involved in a multiple cache recovery scenario. This robust behavior was obtained through the use of a free-flow hierarchy (FFH) as an action selection mechanism. This paper extends BISMARC to include fault tolerance in the sensing and mechanic rover subsystems. The results of simulation studies in a Mars environment are also reported.

关键词： autonomous rovers behavior-based control fault tolerance control hierarchies

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Cooperative robotic sentry vehicles

Cooperative robotic sentry vehicles

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sensor fusion and decentralized control in robotic systems II Conference

作者： Feddema, J Lewis, C Klarer, P Eisler, R Caprihan, R Sandia Natl Labs Intelligent Syst & Robot Ctr Albuquerque NM 87185 USA

ISBN: (纸本)0819434329

As part of a project for the Defense Advanced Research Projects Agency, Sandia National Laboratories' Intelligent systems & robotics Center is developing and testing the feasibility of a cooperative team of robotic sentry vehicles to guard a perimeter and to perform a surround task. This paper describes on-going activities in the development of these robotic sentry vehicles. To date, we have developed a robotic perimeter detection system which consists of eight "Roving All Terrain Lunar Explorer Rovers" (RATLER(TM)), a laptop-based base-station, and several Miniature Intrusion Detection sensors (MIDS). A radio frequency receiver on each of the RATLER vehicles alerts the sentry vehicles of alarms from the hidden MIDS. When an alarm is received, each vehicle decides whether it should investigate the alarm based on the proximity of itself and the other vehicles to the alarm As one vehicle attends an alarm, the other vehicles adjust their position around the perimeter to better prepare for another alarm For the surround task both potential field and A* search path planners have been added to the base-station and vehicles. At the base-station, the operator specifies goal and exclusion regions on a GIS map. The path planner generates vehicle paths that are previewed by the operator. Once the operator has validated the path, the appropriate information is downloaded to the vehicles. For the potential field path planner, the polygons and line segments that represent the obstacles and goals are downloaded to the vehicles, instead of the simulated paths. On board the vehicles, the same potential field path planner generates the path except that it uses the true location of itself and the nearest neighboring vehicle. For the A* path planner, the actual path is downloaded to the vehicles because of limited on-board computational power.

关键词： mobile robots cooperative control distributed autonomous systems

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A modular planning/control architecture for the semi-autonomous control of telerobots in a hazardous environment

A modular planning/control architecture for the semi-autonom...

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Conference on sensor fusion and decentralized control in Autonomous robotic systems

作者： Tarn, TJ Brady, K Xi, N Love, L Lloyd, P Burks, B Davis, H Department of Systems Science and Mathematics Washington University St. Louis MO 63130 United States Oak Ridge National Laboratory Robotics and Process Systems Division Oak Ridge TN 37831-6304 United States

ISBN: (纸本)0819426415

The Oak Ridge National Laboratory (ORNL) has demonstrated, evaluated, and deployed a telerobotic approach for the remote retrieval of hazardous and radioactive wastes from underground storage tanks. The telerobotic system, built by Spar Aerospace Ltd., is capable of dislodging and removing sludge and gravel-like wastes without endangering the human operators through contact with the environment. Working in partnership with Washington University, ORNL has implemented an Event Based Planner/Function Based Sharing control (FBSC) as an integral part of their overall telerobotic architecture. These aspects of the system enable the seamless union of the human operator and an autonomous controller in such a way to emphasize safety without any loss of performance. The cooperation between ORNL, Spar, and Washington University requires an open and modular control software architecture to enable the parallel development of various components of the system. controlShell has been used as the underlying software architecture to help meet these criteria of generality and modularity.

关键词： intelligent control semi-autonomous control teleoperation control systems

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decentralized sensor fusion for Ubiquitous Networking robotics in Urban Areas

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sensorS 2010年第3期10卷 2274-2314页

作者： Sanfeliu, Alberto Andrade-Cetto, Juan Barbosa, Marco Bowden, Richard Capitan, Jesus Corominas, Andreu Gilbert, Andrew Illingworth, John Merino, Luis Mirats, Josep M. Moreno, Plinio Ollero, Anibal Sequeira, Joao Spaan, Matthijs T. J. UPC CSIC Inst Robot & Informat Ind Barcelona Spain Inst Super Tecn Lisbon Portugal Inst Syst & Robot Lisbon Portugal Univ Surrey Ctr Vis Speech & Signal Proc Guildford GU2 5XH Surrey England Pablo Olavide Univ Seville Spain Univ Seville Robot Vis & Control Grp Seville Spain Ctr Adv Aerosp Technol Seville Spain

In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.

关键词： network robot systems distributed sensors robot sensors camera network

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Learning manipulation skills by combining PCA technique and adaptive interpolation

Learning manipulation skills by combining PCA technique and ...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Zhang, JW Knoll, A Univ Bielefeld Fac Technol D-33501 Bielefeld Germany

ISBN: (纸本)0819429848

We propose an approach for learning manipulation skills of robot arms based on complex sensor data. The first component of the used model serves as a projection of high-dimensional input data into an eigenspace by using Principal Component Analysis (PCA). Complex sensor data can be efficiently compressed if robot movements achieving optimal manipulation tasks are constrained to a local scenario. The second component is an adaptive B-spline model whose input space is the eigenspace and whose outputs are robot motion parameters. In the offline learning phase, an appropriate eigenspace can be built by extracting eigenvectors from a sequence of sampling sensor patterns. The B-spline model is then trained for smooth and correct interpolation. In the online application phase, through the cascaded two components, a sensor pattern can be mapped into robot action for performing the specified task. This approach makes tasks such as visually guided positioning much easier to implement. Instead of undergoing cumbersome hand-eye calibration processes, our system is trained in a supervised learning procedure using systematical perturbation motion around the optimal manipulation pose. If more sensors or some robust geometric features from the image processing are available, they can also be added to the input vector. Therefore, the proposed model can integrate multiple sensors and multiple modalities. Our experimental setup is a two-arm robotic system with "self-viewing" hand-eyes and force/torque sensors mounted on each parallel jaw gripper. Implementations with one-hand grasping and two-hand assembly based on visual and force sensors show that the method works even when no robust geometric features can be extracted from the sensor pattern.

关键词： sensor-based skills hand-eye task based mapping learning

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