Abstract

In this paper, an approach to modeling, controller design, and parameter estimation for a self-leveling tripod base is presented. The foldable tripod requires manual set-up and its exact leg positions are therefore unknown, although knowledge of the leg configuration is needed for motion planning and also allows better control of the leveling task. An analysis of the geometry is presented, enabling parameter estimation based on finding the tilt axes of the tripod by moving both actuators separately in sequence. This is then generalized for the estimation from an arbitrary movement of the actuators. Further, a linear state-space model is derived with the estimated parameters, which serves as the basis for LQG controller design. The tripod configuration estimation is experimentally verified and provides sufficient accuracy for both the motion planning and leveling tasks. By using a linear Kalman filter, the leveling control achieves good results despite significant measurement errors caused by structural vibrations.

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