Reduced order modeling of legged locomotion in the horizontal plane Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/xg94hs206

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  • Sprawled-posture insects exhibit a remarkable ability to rapidly run in a stable manner over complex terrain, a feat that has yet to be equaled by man-made legged robots. Recent experimental results suggest that these insects may employ a hierarchical control structure, in which locomotion performance emerges from a combination of insect structure and leg function, which is only augmented by neural reflexes in the presence of large or persistent disturbances. In this study, we utilize a previously developed reduced order model for lateral plane locomotion and extend it by developing leg positioning and actuation strategies that are consistent with insect leg function evidenced in experiments. We examine improvements in locomotion performance obtained by utilizing these strategies in terms of gait stability and robustness to external perturbations, such as those that might be encountered when running over rough terrain. Leg positioning strategies examined include leg angle control based upon previous leg angles and leg recirculation strategies that prescribe, in a feedforward manner, the motion of the leg as it swings from its lift-off to touch-down positions. Both these protocols provide control authority in re-orienting system momentum and are shown to improve gait stability and robustness to external perturbations. While the original reduced order template models leg dynamics by an energy-conserving spring, we incorporate energetic variations through leg actuation that varies the force-free leg length during the stance phase while preserving qualitatively correct force and velocity profiles. In contrast to the partially asymptotically stable gaits identified in previous analyses, incorporating leg actuation in conjunction with the leg positioning strategies produces completely asymptotically stable gaits in body coordinates. Locomotion performance of the resulting model is subsequently analyzed by computing the basin of stability of our model in response to energetic perturbations of the type experimentally implemented on running, sprawled-posture insects.
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