We address the problem of coordinating the activities of a team of agents in a dynamic, uncertain, nonlinear environment. Bounded rationality, bounded communication, subjectivity and distribution make it extremely challenging to find effective strategies. In these domains it is difficult to accurately predict whether potential policy modifications will lead to an increase in the value of the team reward. Our Predictability and Criticality Metrics (PCM) approach errs on the side of safety, and advocates considering policy modifications that are guaranteed to not harm the current policy, and uses simple metrics to choose from within that set a modification that increases the team reward. In the context of the DARPA Coordinators program, we show how the PCM approach yielded a system that significantly outperformed several competing approaches in an extensive independent evaluation.
The paper describes a target tracking system running on a Heterogeneous Sensor Network (HSN) and presents results gathered from a realistic deployment. The system fuses audio direction of arrival data from mote class devices and object detection measurements from embedded PCs equipped with cameras. The acoustic sensor nodes perform beamforming and measure the energy as a function of the angle. The camera nodes detect moving objects and estimate their angle. The sensor detections are sent to a centralized sensor fusion node via a combination of two wireless networks. The novelty of our system is the unique combination of target tracking methods customized for the application at hand and their implementation on an actual HSN platform.
Many wireless sensor network applications require knowledge of node placement in order to make sense of sensor data in a spatial context. Networks of mobile sensors require position updates for navigation through the sensing region. The global positioning system is able to provide localization information, however in many situations it cannot be relied on, and alternative localization methods are required. We propose a technique for the localization and navigation of a mobile robot that uses the Doppler-shift in frequency observed by stationary sensor nodes. Our experimental results show that, by using observed RF Doppler shifts, a robot is able to navigate through a sensing region with an average localization error of 1.68 meters.
The application of model-based diagnosis schemes to real systems introduces many significant challenges, such as building accurate system models for heterogeneous systems with complex behaviors, dealing with noisy measurements and disturbances during system operation, and producing valuable results in a timely manner with limited information and computational resources. The Advanced Diagnostics and Prognostics Testbed (ADAPT), deployed at NASA Ames Research Center, is a representative spacecraft electrical power distribution system that embodies a number of these challenges for developing realistic diagnosis and prognosis algorithms. ADAPT contains a large number of interconnected components, along with a number of circuit breakers and relays that enable a number of different power distribution configurations. The system includes electrical dc and ac loads, mechanical subsystems, such as motors, and fluid systems, such as pumps. The system components are susceptible to different types of faults that include unexpected changes in parameter values, discrete faults in switching elements, and sensor faults. This paper presents Hybrid TRANSCEND, a comprehensive model-based diagnosis scheme to address these challenges. The scheme uses the hybrid bond graph modeling language to systematically develop computational models and algorithms for hybrid state estimation, robust fault detection, and efficient fault isolation. The computational methods are implemented as a suite of software tools that enables analysis and testing through simulation, diagnosability studies, and deployment on the experimental testbed. Simulation and experimental results demonstrate the effectiveness of this methodology in efficient diagnosis of heterogeneous components for an embedded system.
We observe that the e-business systems development frameworks tradeoff performance at the expense of flexibility. In this paper, we present a performance comparison of JavaBeans application framework with a well-known framework, Struts. JavaBeans is a flexible and extensible CBD application framework. However the flexibility and extensibility are conflicting software qualities against the performance. Our experiment results show the significance of JavaBeans application framework over contemporary CBD application frameworks and how much its performance is affected by changing schemes of the framework for achieving flexibility and extensibility.
Effective resource management for distributed real-time embedded (DRE) systems is hard due to their unique characteristics, including (1) constraints in multiple resources and (2) highly fluctuating resource availability and input workload. DRE systems can benefit from a middleware framework that enables adaptive resource management algorithms to ensure application QoS requirements are met. This paper identifies key challenges in designing and extending resource allocation algorithms for DRE systems. We present an empirical study of bin-packing algorithms enhanced to meet these challenges. Our analysis identifies input application patterns that help generate appropriate heuristics for using these algorithms effectively in DRE systems.
Real-life Cyber-Physical Systems (CPSs), such as automotive vehicles, building automation systems, and groups of unmanned air vehicles are monitored and controlled by networked control systems. The overall system dynamics emerges from the interaction among physical dynamics, computational dynamics, and communication networks. Network uncertainties such as time-varying delay and packet loss cause significant challenges that probihibit the application of traditional component based design methods. This paper proposes a passive control architecture for designing CPSs that are insensitive to network uncertainties. The proposed method improves orthogonality across the controller design and implementation design layers with respect to network uncertainties, thus empowering model driven development. The paper presents the architecture for a simplified system consisting of a robotic manipulator controlled by a digital controller over a wireless network and simulation results that show that the system is insensitive to time-varying network delays.
This paper provides a framework to synthesize lm2-stable and Lm2-stable control networks in which m strictly-output passive controllers can control n - m strictly-output passive plants. The communication between the plants and controllers can tolerate time varying delay and data dropouts. In particular, we introduce a power junction which allows even a single controller (typically designed to control a single plant) to accurately control the position of multiple plants even if the dynamics of the plants are different. An illustrative simulated example shows the position tracking performance of the system. We conclude the discussion with two questions for future research.
Sensor networks are distributed real-time embedded (DRE) systems that often operate in open environments where operating conditions, workload, resource availability, and connectivity cannot be accurately characterized a priori. As with other open DRE systems, they must perform sequences of heterogeneous data collection, manipulation, and coordination tasks to meet specified system objectives. The South East Alaska MOnitoring Network for Science, Telecommunications, Education, and Research (SEAMONSTER) project illustrates many common system management and dynamic operation challenges in a representative sensor network, including adapting to changes in network topology, effective reaction to local environmental changes, and power management through system sleep/wake cycles. This paper discusses a case study for applying middleware and autonomous agent technologies from the Multi-agent Architecture for Coordinated Responsive Observations (MACRO) to these challenges in the SEAMONSTER sensor network.
Localization and tracking of wireless nodes have been active research areas in robotics, mobile ad-hoc networks, and wireless sensor networks. While several phenomena have been utilized for this purpose, RF signals have many advantages. Signal strength and time-of-flight are the two typical ways of extracting range information. Recently, radio interferometry was proposed to solve this problem using phase and/or Doppler shift measurements across severely resource-constrained devices. The former requires many measurements at multiple frequencies, while the latter needs motion to generate a usable signal. This paper introduces a novel ranging method based on a rotating antenna generating a Doppler shifted RF signal. The frequency change can be measured using the radio interferometric technique even on low-cost, resource constrained devices. This simple idea provides a surprising number of different ways for estimating range and location. The paper outlines these techniques and describes one of them in more detail with experimental and simulation results.