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Estimators for micro-robot leg dynamics with uncertain jump conditions and infrequent sampling

This paper examines estimation of micro-robotic leg dynamics across uncertain ground impact conditions. A model for impact of compliant micro-structures with unknown ground geometries is adapted to a switched system format having explicit random parameters associated with uncertain impact conditions. Estimation schemes for dynamic states of the robot leg are derived based on Kalman filtering, including a novel ad hoc method for incorporating inter-sample impact events based on linear interpolations. Model and estimation schemes are tested against experimental motion of a meso-scale compliant piezoelectric robot test bed. The impact model improves on prior modeling techniques in capturing mean impact time and variability of step height, though impact time variation is overstated in open-loop. Impact time estimates are much improved using the estimator with inter-sample events, though estimation error over the entirety of leg motion is inferior to that of a more conventional hybrid Kalman filter.