Real-time binocular smooth pursuit
International Journal of Computer Vision
Self-adaptive software for signal processing
Communications of the ACM
Real-time tracking of moving objects with an active camera
Real-Time Imaging - Special issue on computer vision motion analysis
Coordinating agent activities in knowledge discovery processes
WACC '99 Proceedings of the international joint conference on Work activities coordination and collaboration
Guest Editor's Introduction: Creating Robust Software through Self-Adaptation
IEEE Intelligent Systems
Control Theory-Based Foundations of Self-Controlling Software
IEEE Intelligent Systems
An Architecture-Based Approach to Self-Adaptive Software
IEEE Intelligent Systems
Distributed Control Representation for Manipulation Tasks
IEEE Expert: Intelligent Systems and Their Applications
W4S: A real-time system detecting and tracking people in 2 1/2D
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Geometrical Modeling and Real-Time Vision Applications of a Panoramic Annular Lens (PAL) Camera System
Specifying Coordination Processes Using Little-JIL TITLE2:
Specifying Coordination Processes Using Little-JIL TITLE2:
A Fault-Tolerant Distributed Vision System Architecture for Object Tracking in a Smart Room
ICVS '01 Proceedings of the Second International Workshop on Computer Vision Systems
Technological research plan for active ageing
Information Systems Frontiers
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Robot control in nonlinear and nonstationary run-time environments presents challenges to traditional software methodologies. In particular, robot systems in "open" domains can only be modeled probabilistically and must rely on run-time feedback to detect whether hardware/software configurations are adequate. Modifications must be effected while guaranteeing critical performance properties. Moreover, in multi-robot systems, there are typically many ways in which to compensate for inadequate performance. The computational complexity of high dimensional sensorimotor systems prohibits the use of many traditional centralized methodologies. We present an application in which a redundant sensor array, distributed spatially over an office-like environment can be used to track and localize a human being while reacting at run-time to various kinds of faults, including: hardware failure, inadequate sensor geometries, occlusion, and bandwidth limitations. Responding at run-time requires a combination of knowledge regarding the physical sensorimotor device, its use in coordinated sensing operations, and high-level process descriptions. We present a distributed control architecture in which run-time behavior is both preanalyzed and recovered empirically to inform local scheduling agents that commit resources autonomously subject to process control specifications. Preliminary examples of system performance are presented from the UMass Self-Adaptive Software (SAS) platform.