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.