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This work presents an approach to plan motion strategies for robotics tasks constrained by uncertainty in position, orientation, and control. Our approach operates in a (z, y, 0) configuration space and it combines two local functions: a contact-based attraction function and an exploration function. Compliant motions are used to reduce the positiodorientation uncertainty. An explicit geometric model for the uncertainty is defined to evaluate the reachability of the obstacle surfaces when the robot translates in free space.

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In this paper the design of a robust controller for position control in machining for a HEXAGLIDE type parallel robot using Quantitative Feedback Theory (QFT) is presented.The work is motivated by the insufficient vibration reduction achieved with a standard PID controller. Therefore active and passive disturbance rejection is the main objective.The linearization procedure of a detailed symbolic multibody model is presented and the disturbances --in QFT terminology--appearing as a result of the linearization shown. Uncertainties related to plant position, viscous friction coefficients and drive gains are considered. As a key step to a successful QFT design, special care is user to describe and quantify any known source of disturbances.Relative Gain Analysis is used to justify the adoption of a simplified SISO control design paradigm, and the coupling between axes quantified as a relatively small source of disturbances.Stability, control effort, disturbance rejection, and tracking performance are used to define the optimum minimum gain controller. The criteria is adjusted having in mind the capabilities of the plant and the importance of the different sources of disturbances.Virtual multibody simulations of the designed controller along with the nonlinear model of the plant are presented assessing the validity of the controller. The designed controller is intended to be deployed in the real manipulator and implemented using RTAI Linux Real Time implementation within the the EMC2 machine control software.