Intelligent self-situational awareness refers to the ability of a system to autonomously assess its health and condition and to interpret the impact of its current and future health and condition on current mission ob...
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ISBN:
(纸本)1563477270
Intelligent self-situational awareness refers to the ability of a system to autonomously assess its health and condition and to interpret the impact of its current and future health and condition on current mission objectives. Intelligent self-situational awareness represents a fusion of system health monitoring and intelligent autonomouscontrol and is an extension of embedded diagnostics and prognostics, integrated system health management, and condition based maintenance that incorporates not only the ability to perceive current health and condition, but to assess the impact of the current health and condition within the context of the current mission requirements and resources. Department of Defense investment in system health management has been driven largely by a desire to reduce manning and control operational and sustainment costs associated with maintenance and logistics over the life cycle of systems. Studies conducted by the Applied Research Laboratory have shown payback times of 3-4 years for the investment in system health management for major platforms with significant cost savings and 4-5% improvements in operational availability.1 In order to implement integrated system health management in unmanned systems, the health monitoring capability must be integrated with the autonomouscontrol system to avoid the bandwidth requirements and communication delays associated with sending health and performance-related sensor data back to a human operator. The capability of intelligent self-situational awareness can reduce the cognitive load on humans in manned and collaborative human-robotic missions, reduce the work load for ground support personnel, provides increased ability to respond to unanticipated faults and system degradation, and aid in mission planning and implementation. The benefits associated with the use of traditional embedded diagnostics and prognostics will still apply in space exploration missions: reduced loss of system availability due to
This paper concerns the problem of actively searching for and localizing ground features by a coordinated team of air and ground roboticsensor platforms. The approach taken builds on well known decentralized Data Fus...
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This paper concerns the problem of actively searching for and localizing ground features by a coordinated team of air and ground roboticsensor platforms. The approach taken builds on well known decentralized Data fusion (DDF) methodology. In particular, it brings together established representations developed for identification and linearized estimation problems to jointly address feature detection and localization. This provides transparent and scalable integration of sensor information from air and ground platforms. As in previous studies, an Information-theoretic utility measure and local control strategy drive the robots to uncertainty reducing team configurations. Complementary characteristics in terms of coverage and accuracy are revealed through analysis of the observation uncertainty for air and ground on-board cameras. Implementation results for a detection and localization example indicate the ability of this approach to scalably and efficiently realize such collaborative potential.
The paper presents an algorithm for Bayesian decentralized data fusion (BDDF) and its extension to information-theoretic control. The algorithm is stated for a feature represented by a general probability density func...
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ISBN:
(纸本)917056115X
The paper presents an algorithm for Bayesian decentralized data fusion (BDDF) and its extension to information-theoretic control. The algorithm is stated for a feature represented by a general probability density function. Several specific representations are then considered - Gaussian, discrete, Certainty Grid, and hybrid. Well known algorithms for these representations are shown to fit the general BDDF pattern. Stating the algorithms in Bayesian terms has a practical advantage of allowing a generic software implementation. It is also hoped that a clear general formulation will stimulate extensions to efficient non-parametric representations of arbitrary distributions. The algorithms are described in the context of the Active sensor Network architecture - a modular framework for decentralized cooperative data fusion and control. The approach is illustrated with the results of two deployment scenarios with an indoor sensor network.
With increasing demand for flexibility, ability to handle complicated tasks, and dexterity, modern roboticsystems have become inherently complex and non-linear. This calls for developing enhanced robust algorithms fo...
With increasing demand for flexibility, ability to handle complicated tasks, and dexterity, modern roboticsystems have become inherently complex and non-linear. This calls for developing enhanced robust algorithms for fusing sensor data, developing model-free, goal-driven, and universally applicable controllers capable of self-learning, and making use of several robots to improve task-handling capability of the system. This dissertation deals with significant issues involved in three key areas in robotics: (i) sensorfusion, (ii) Intelligent control Techniques (e.g., Fuzzy Logic control), and (iii) Multiple Manipulator control. The research presented in this dissertation formulates an analytical foundation for capturing uncertainties involved in sensor measurements in the form of sensor model, and uses that information to combine data from multiple sensors in a Bayesian framework to obtain consistent and accurate description of quantities of interest. An innovative neural network based calibration method has been proposed to obtain three-dimensional positional information in robot coordinate frame using a stereo setting. Furthermore, the research makes use of three vision sensors and a proximity sensor to obtain an occupancy profile to validate the sensorfusion strategies. The research also utilizes Kalman filtering technique to incorporate dynamics of end effector for accurate estimation of forces and moments acting at the tip of the robot grippers. This research develops an analytical foundation for controlling multiple industrial robots working cooperatively in a fully automated manufacturing work cell. The absence of complete information on dynamic parameters of the robots has inspired the use of a model-free intelligent control technique such as fuzzy logic control. The research proposes a strategy based on artificial neural networks to learn and optimize fuzzy logic rule base and membership function parameters. The proposed neuro-fuzzy scheme uses a backprop
Air and ground vehicles exhibit complementary capabilities and characteristics as roboticsensor platforms. Fixed wing aircraft offer broad field of view and rapid coverage of search areas. However, minimum operating ...
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ISBN:
(纸本)0819455628
Air and ground vehicles exhibit complementary capabilities and characteristics as roboticsensor platforms. Fixed wing aircraft offer broad field of view and rapid coverage of search areas. However, minimum operating airspeed and altitude limits, combined with attitude uncertainty, place a lower limit on their ability to detect and localize ground features. Ground vehicles on the other hand offer high resolution sensing over relatively short ranges with the disadvantaue of slow coverage. This paper presents a decentralized architecture and solution methodology for seamlessly realizing the collaborative potential of air and ground roboticsensor platforms. We provide a framework based on an established approach to the underlying sensorfusion problem. This provides transparent integration of information from heterogeneous sources. An information-theoretic utility measure captures the task objective and robot inter-dependencies. A simple distributed solution mechanism is employed to determine team member sensing trajectories subject to the constraints of individual vehicle and sensor sub-systems. The architecture is applied to a mission involving searching for and localizing an unknown number of targets in an user specified search area. Results for a team of two fixed wing UAVs and two all terrain UGVs equipped with vision sensors are presented.
The wireless intelligent monitoring and analysis systems is a proof-of-concept directed at discovering solution(s) for providing decentralized intelligent data analysis and control for distributed containers equipped ...
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ISBN:
(纸本)0819453579
The wireless intelligent monitoring and analysis systems is a proof-of-concept directed at discovering solution(s) for providing decentralized intelligent data analysis and control for distributed containers equipped with wireless sensing units. The objective was to embed smart behavior directly within each wireless sensor container, through the incorporation of agent technology into each sensor suite. This approach provides intelligent directed fusion of data based on a social model of teaming behavior. This system demonstrates intelligent sensor behavior that converts raw sensor data into group knowledge to better understand the integrity of the complete container environment. The emergent team behavior is achieved with lightweight software agents that analyze sensor data based on their current behavior mode. When the system starts-up or is reconfigured the agents self-organize into virtual random teams based on the leader/member/lonely paradigm. The team leader collects sensor data from their members and investigates all abnormal situations to determine the legitimacy of high sensor readings. The team leaders flag critical situation and report this knowledge back to the user via a collection of base stations. This research provides insight into the integration issues and concerns associated with integrating multi-disciplinary fields of software agents, artificial life and autonomoussensor behavior into a complete system.
This paper describes the techniques for command and control of autonomous mobile vehicle robots using a mobile phone and a mobile computer via Internet. The autonomous unmanned ground vehicle robot(UGV) developed at A...
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This paper describes the techniques for command and control of autonomous mobile vehicle robots using a mobile phone and a mobile computer via Internet. The autonomous unmanned ground vehicle robot(UGV) developed at Artificial Life and robotics Laboratory of The University of Oita is called "Tarou". We show the techniques for Tarou to perform the tasks as follows;(1) an efficient sensorfusion from many sensors(vision, audio, geographic, etc.), (2) synthesizing and understanding the data including on-line image obtained from sensors installed with Tarou, (3) formulate the next course of action. The techniques developed enable Tarou to obtain the powerful ability for autonomous sensing and dynamic mobility for locomotion and navigation. The experiments for sending command and control to Tarou's tasks were performed successfully by the public Internet. The techniques developed could dramatically increase the performance of the autonomous unmanned ground vehicle robots for a future robotic defense system need.
This paper presents a fully automated and decentralized surveillance system for the problem of detecting and possibly tracking mobile unknown ground vehicles in a bounded area. The system consists ideally of unmanned ...
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ISBN:
(纸本)0819453269
This paper presents a fully automated and decentralized surveillance system for the problem of detecting and possibly tracking mobile unknown ground vehicles in a bounded area. The system consists ideally of unmanned aerial vehicles (UAVs) and unattended fixed sensors with limited communication and detection range that are deployed in the area of interest. Each component of the system (UAV and/or sensor) is completely autonomous and programmed to scan the area searching for targets and share its knowledge with other components within communication ran,e. We assume that both UAVs and sensors have similar computing and sensing capabilities and differ only in their mobility (sensors are stationary while UAVs are mobile). Gathered information is reported to a base station (monitor) that computes an estimate of the global state of the system and quantifies the quality of the surveillance based on a measure of the uncertainty on the number and position of the targets overtime. The present solution has been achieved through a robotic implementation of a software simulation that was in turn realized under the principles of a novel top-down methodology for the design of provably performant agent-based controlsystems. In this paper we provide a description of our solution including the distributed algorithms that have been employed in the control of the UAV navigation and monitoring. Finally we show the results of an novel experimental performance analysis of our surveillance system.
Designing autonomous Mobile Robots introduces the reader to the fundamental concepts of this complex field. The author addresses all the pertinent topics of the electronic hardware and software of mobile robot design,...
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ISBN:
(数字)9780080477183
ISBN:
(纸本)9780750676830
Designing autonomous Mobile Robots introduces the reader to the fundamental concepts of this complex field. The author addresses all the pertinent topics of the electronic hardware and software of mobile robot design, with particular emphasis on the more difficult problems of control, navigation, and sensor interfacing. Covering topics such as advanced sensorfusion, controlsystems for a wide array of application sensors and instrumentation, and fuzzy logic applications, this volume is essential reading for engineers undertaking robotics projects as well as undergraduate and graduate students studying robotic engineering, artificial intelligence, and cognitive science. Its state-of-the-art treatment of core concepts in mobile robotics helps and challenges readers in exploring new avenues in an exciting field. Authored by a well-known pioneer of mobile robotics Learn how to approach the design of and complex control system with confidence
The paper presents a decentralized approach to the solution of the distributed information gathering problem. The main design objectives are scalability with the number of network components, maximum flexibility in im...
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The paper presents a decentralized approach to the solution of the distributed information gathering problem. The main design objectives are scalability with the number of network components, maximum flexibility in implementation and deployment, and robustness to component and communication failure. The design approach emphasizes interactions between components rather than the definition of the components themselves. The architecture specifies a small set of interfaces sufficient to implement a wide range of information gathering systems. The results of two deployment scenarios on an indoor sensor network are presented.
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