Browsing by Author "Hamilton, Deirdre Lynne"

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    Effectiveness and performance analysis of a class of parallel robot controllers with fault tolerance
    (1996) Hamilton, Deirdre Lynne; Walker, Ian D.; Bennett, John K.
    In the past, robots were only applied to simple repetitive tasks, such as assembly line work. However robotics research now encompasses a broad spectrum of application possibilities. Robots are being considered for use in more advanced manufacturing applications, medical and space applications, and numerous other tasks. Speed and precision of control are two primary issues for current and future applications of robotic systems. Fault tolerance is also increasingly important for many robot tasks. This work focuses on improving the efficiency and fault tolerance capabilities of robot controllers. Here we address the following questions: "How can robot control be improved from the perspective of the algorithm implementation? What combination of speed and precision can we achieve for good overall performance?" Due to the coupling in the dynamics equations, coarse-grain parallelization of robot control algorithms is particularly difficult. In this thesis, we develop a new parallel control algorithm for robots based on the Newton-Euler dynamics formulation that overcomes the serial nature of these equations, allowing a high level of parallelism. Our controller uses data from a previous control step in current calculations to allow many more tasks to be executed in parallel, thus providing higher control update rates. The use of 'stale' data is an effective solution to the speedup problem, but presents some special difficulties. A stability issue when using 'stale' data that is encountered in previous algorithm approaches is discussed here. The incorporation of fault tolerance techniques into robot systems improves the reliability, but also increases the hardware and computational requirements in the overall system. Since all of these things affect system design, it is not always clear how to evaluate the merit, or 'effectiveness' of different fault tolerance approaches for a given application. In this thesis, we present a new set of performance criteria designed to measure and compare the effectiveness of robot fault tolerance strategies. The measures, which are designed to evaluate fault tolerance/performance/cost tradeoffs, can also be used to evaluate pure performance or pure fault tolerance strategies. We show their usefulness using a variety of proposed fault tolerance approaches in the literature, focusing on multiprocessor control architectures.
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    Performance and reliability of a parallel robot controller
    (1992) Hamilton, Deirdre Lynne; Bennett, John K.; Walker, Ian D.
    Most robot controllers today are uniprocessor architectures. As robot control algorithms become more complex, these serial controllers have difficulty providing the desired response times. Additionally, with robots being used in environments that are hazardous or inaccessible to humans, fault-tolerant robotic systems are particularly desirable. A uniprocessor control architecture cannot offer tolerance of processor faults. Use of multiple processors for robot control offers two advantages over single processor systems. Parallel control provides a faster response, which in turn allows a finer granularity of control. Processor fault tolerance is also made possible by the existence of multiple processors. There is a trade-off between performance and level of fault tolerance provided. The work of this thesis shows that a shared memory multiprocessor robot controller can provide higher performance than a uniprocessor controller, as well as processor fault tolerance. The trade-off between these two attributes is also demonstrated.