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IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications, MESA

作者： Stephen S. Nestinger David Ko Alex Rumer Harry H. Cheng Department of Mechanical and Aeronautical Engineering University of California Davis Davis CA USA Department of Mechanical and Aeronautical Engineering University of California슠Davis Davis CA USA

Vision systems have become popular for remote vision sensing in geographically distributed environments due to vast amount of information they provide. However, remote vision sensors are generally plagued with power and communication bandwidth constraints. Mobile agent technology is a salient solution to geographically distributed and dynamic domains that require subsystems to interact with each other. Mobile agent technology increases power efficiency by reducing communication requirements and increases fusion processing by allowing in-situ integration of on-demand visual processing and analysis algorithms. A mobile agent can dynamically migrate from one vision sensor to another and combine all necessary sensor data in a desired manner specific to the system requesting the data. This paper presents a remote vision fusion architecture based on mobile agent technology that provides a flexible vision fusion solution. The architecture utilizes the Mobile-C library as a basis for the mobile agency along with OpenCV and ImageMagick for vision processing and manipulation. An application example is provided that demonstrates the benefit of using mobile agents for vision fusion in remote vision systems. The validity of the architecture is proven in an experimental setup with a retrofitted robotic cell comprised of a Puma 560, IBM 7575, a conveyor system, and a vision system.

关键词： sensor fusion Machine vision sensor systems Mobile agents Robot sensing systems Mobile robots Robot vision systems Mobile communication Electrical equipment industry Industrial control

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Tier-scalable reconnaissance: The challenge of sensor optimization, sensor deployment, sensor fusion, and sensor interoperability

Tier-scalable reconnaissance: The challenge of sensor optimi...

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Conference on Micro (MEMS) and Nanotechnologies for Defense and Security

作者： Fink, Wolfgang George, Thomas Tarbell, Mark A. CALTECH Visual & Autonomous Explorat Syst Res Lab Div Phys Math & Astron 1200 E Calif BlvdMail Code 103-33 Pasadena CA 91125 USA ViaLogy LLC Altadena CA 91001 USA

ISBN: (纸本)9780819466785

robotic reconnaissance operations are called for in extreme environments, not only those such as space, including planetary atmospheres, surfaces, and subsurfaces, but also in potentially hazardous or inaccessible operational areas on Earth, such as mine fields, battlefield environments, enemy occupied territories, terrorist infiltrated environments, or areas that have been exposed to biochemical agents or radiation. Real time reconnaissance enables the identification and characterization of transient events. A fundamentally new mission concept for tier-scalable reconnaissance of operational areas, originated by Fink et al., is aimed at replacing the engineering and safety constrained mission designs of the past. The tier-scalable paradigm integrates multi-tier (orbit double left right arrow atmosphere double left right arrow surface/subsurface) and multi-agent (satellite double left right arrow UAV/blimp double left right arrow surface/subsurface sensing platforms) hierarchical mission architectures, introducing not only mission redundancy and safety, but also enabling and optimizing intelligent, less constrained, and distributed reconnaissance in real time. Given the mass, size, and power constraints faced by such a multi-platform approach, this is an ideal application scenario for a diverse set of MEMS sensors. To support such mission architectures, a high degree of operational autonomy is required. Essential elements of such operational autonomy are: (1) automatic mapping of an operational area from different vantage points (including vehicle health monitoring);(2) automatic feature extraction and target/region-of-interest identification within the mapped operational area;and (3) automatic target prioritization for close-up examination. These requirements imply the optimal deployment of MEMS sensors and sensor platforms, sensor fusion, and sensor interoperability.

关键词： tier-scalable reconnaissance space exploration hazardous environment mission autonomy integrated vehicle health management multi-parameter optimization design/performance optimization (MEMS) sensors sensor fusion sensor interoperability

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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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IEEE/RSJ International Conference on Intelligent Robots and Systems

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

ISBN: (纸本)9781424402588

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 (EIKF) framework We present simulation and experimental results of 2D deployment scenarios using low-cost mobile sensor robots developed in our lab.

关键词： adaptive sampling sensor fusion Kalman filter environmental monitoring

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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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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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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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International Conference on Control, Automation, robotics and Vision (ICARCV)

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

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： Sampling methods Mobile robots Robot sensing systems Wireless sensor networks Sea measurements sensor phenomena and characterization robotics and automation sensor fusion Monitoring Chemical and biological sensors

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Intelligent and efficient strategy for unstructured environment sensing using mobile robot agents

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JOURNAL OF INTELLIGENT & robotic SYSTEMS 2005年第2-4期43卷 217-253页

作者： Sujan, VA Meggiolaro, MA Cummins Engine Co Air Handling & Combust Control Div Columbus IN 47201 USA Pontificia Univ Catolica Rio de Janeiro Dept Mech Engn BR-22453900 Rio De Janeiro Brazil

In field environments it is not usually possible to provide robots in advance with valid geometric models of its task and environment. The robot or robot teams need to create these models by scanning the environment with its sensors. Here, an information-based iterative algorithm to plan the robot's visual exploration strategy is proposed to enable it to most efficiently build 3D models of its environment and task. The method assumes mobile robot (or vehicle) with vision sensors mounted at a manipulator end-effector (eye-in-hand system). This algorithm efficiently repositions the systems' sensing agents using an information theoretic approach and fuses sensory information using physical models to yield a geometrically consistent environment map. This is achieved by utilizing a metric derived from Shannon's information theory to determine optimal sensing poses for the agent(s) mapping a highly unstructured environment. This map is then distributed among the agents using an information-based relevant data reduction scheme. This method is particularly well suited to unstructured environments, where sensor uncertainty is significant. Issues addressed include model-based multiple sensor data fusion, and uncertainty and vehicle suspension motion compensation. Simulation results show the effectiveness of this algorithm.

关键词： visual mapping cooperative robots information theory unstructured environments data fusion

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Intelligent robotic sensor agents for environment monitoring

Intelligent Robotic Sensor Agents for environment monitoring

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IEEE International Symposium on Virtual and Intelligent Measurement Systems

作者： Petriu, EM Patry, GG Whalen, TE Al-Dhaher, A Groza, VZ Univ Ottawa Ottawa ON K1N 6N5 Canada

ISBN: (纸本)0780373448

This paper discusses development aspects of a wireless network of mobile autonomous robotic Intelligent sensor agents deployed in the field for active investigation of multiple environmental parameters. The collected sensor data are fused in a world model, which is available to remote human supervisors as an interactive virtual Virtualized Reality(TM) environment model.

关键词： intelligent sensors mobile agents distributed sensor networks wireless sensors multi-sensor data fusion behavior-based robots Virtualized Reality(TM) human computer interaction

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An open multi-agent control architecture to support virtual reality based man-machine interfaces

An open multi-agent control architecture to support virtual ...

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sensor fusion and Decentralized Control in robotic Systems IV Conference

作者： Freund, E Rossmann, R Brasch, M Univ Dortmund Inst Robot Res D-44227 Dortmund Germany

ISBN: (纸本)0819442992

Projective Virtual Reality(2) is a new and promising approach to intuitively operable man machine interfaces for the commanding and supervision of complex automation systems. The user interface part of Projective Virtual Reality heavily builds on latest Virtual Reality techniques, a task deduction component and automatic action planning capabilities. In order to realize man machine interfaces for complex applications, not only the Virtual Reality part has to be considered but also the capabilities of the underlying robot and automation controller are of great importance. This paper presents a control architecture that has proved to be an ideal basis for the realization of complex robotic and automation systems that are controlled by Virtual Reality based man machine interfaces. The architecture does not just provide a well suited framework for the real-time control of a multi robot system but also supports Virtual Reality metaphors and augmentations which facilitate the user's job to command and supervise a complex system. The developed control architecture has already been used for a number of applications. Its capability to integrate sensor information from sensors of different levels of abstraction in real-time helps to make the realized automation system very responsive to real world changes. In this paper, the architecture will be described comprehensively, its main building blocks will be discussed and one realization that is built based on an open source real-time operating system will be presented. The software design and the features of the architecture which make it generally applicable to the distributed control of automation agents in real world applications will be explained. Furthermore its application to the commanding and control of experiments in the Columbus space laboratory, the European contribution to the International Space Station (ISS), is only one example which will be described.

关键词： Projective Virtual Reality robot controller real-time-capability distributed system International Space Station man-machine-interface

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An expectation-based framework of object schemas and port-based agents for disparate feedback assimilation

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AUTONOMOUS ROBOTS 1999年第2期7卷 159-173页

作者： Nelson, BJ Khosla, PK Univ Minnesota Dept Mech Engn Minneapolis MN 55455 USA Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

robotic manipulation systems that operate in unstructured environments must be responsive to feedback from sensors that are disparate in both location and modality. This paper describes a distributed framework for assimilating the disparate feedback provided by force and vision sensors, including active vision sensors, for robotic manipulation systems. The main components of the expectation-based framework include object schemas and port-based agents. Object schemas represent the manipulation task internally in terms of geometric models with attached sensor mappings. Object schemas are dynamically updated by sensor feedback, and thus provide an ability to perform three dimensional spatial reasoning during task execution. Because object schemas possess knowledge of sensor mappings, they are able to both select appropriate sensors and guide active sensors based on task characteristics. Port-based agents are the executors of reference inputs provided by object schemas and are defined in terms of encapsulated control strategies. Experimental results demonstrate the capabilities of the framework in two ways: the performance of manipulation tasks with active camera-lens systems, and the assimilation of force and vision sensory feedback.

关键词： force control visual serving sensor fusion robotic manipulation active sensors

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