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This paper is directed towards developing human-machine cooperative systems (HCMS) for augmented surgical manipulation tasks. These tasks are commonly repetitive, sequential, and consist of simple steps. The transitions between these steps can be driven either by the surgeon's input or sensory information. Consequently, complex tasks can be effectively modeled using a set of basic primitives, where each primitive defines some basic type of motion (e.g. translational motion along a line, rotation about an axis, etc.). These steps can be "open-loop" (simply complying to user's demands) or "closed-loop, in which case external sensing is used to define a nominal reference trajectory. The particular research problem considered here is the development of a system that supports simple design of complex surgical procedures from a set of basic control primitives. The three system levels considered are: i) task graph generation which allows the user to easily design or model a task, ii) task graph execution which executes the task graph, and iii) at the lowest level, the specification of primitives which allows the user to easily specify new types of primitive motions. The system has been developed and validated using the JHU Steady Hand Robot as an experimental platform.