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This paper describes a test-bed for planar micro and mesoscale manipulation tasks and a framework for planning based on quasi-static models of mechanical systems with intermittent frictional contacts. We show how planar peg-in-the-hole assembly tasks can be designed using randomized motion planning techniques with Mason's models for quasi-static manipulation. Simulation and experimental results are presented in support of our methodology. We develop this further into a systematic approach to incorporating uncertainty into planning manipulation tasks with frictional contacts. We again consider the canonical problem of assembling a peg into a hole at the mesoscale using probes with minimal actuation but with visual feedback from an optical microscope. We consider three sources of uncertainty. First, because of errors in sensing position and orientation of the parts to be assembled, we must consider uncertainty in the sensed configuration of the system. Second, there is uncertainty because of errors in actuation. Third, there are geometric and physical parameters characterizing the environment that are unknown. We discuss the synthesis of robust planning primitives using a single degree-of-freedom probe and the automated generation of plans for mesoscale manipulation. We show simulation and experimental results of our work.