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Footstep Adjustment for Biped Push Recovery on Slippery Surfaces

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arxiv 2111.05203 v1 pith:FVGQWPDM submitted 2021-11-09 cs.RO cs.SYeess.SY

classification cs.ROcs.SYeess.SY
keywords surfacespushrecoverystabilitysurfaceaccountcomputationalconditions
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Despite extensive studies on motion stabilization of bipeds, they still suffer from the lack of disturbance coping capability on slippery surfaces. In this paper, a novel controller for stabilizing a bipedal motion in its sagittal plane is developed with regard to the surface friction limitations. By taking into account the physical limitation of the surface in the stabilization trend, a more advanced level of reliability is achieved that provides higher functionalities such as push recovery on low-friction surfaces and prevents the stabilizer from overreacting. The discrete event-based strategy consists of modifying the step length and time period at the beginning of each footstep in order to reestablish stability necessary conditions while taking into account the surface friction limitation as a constraint to prevent slippage. Adjusting footsteps to prevent slippage in confronting external disturbances is perceived as a novel strategy for keeping stability, quite similar to human reaction. The developed methodology consists of rough closed-form solutions utilizing elementary math operations for obtaining the control inputs, allowing to reach a balance between convergence and computational cost, which is quite suitable for real-time operations even with modest computational hardware. Several numerical simulations, including push recovery and switching between different gates on low-friction surfaces, are performed to demonstrate the effectiveness of the proposed controller. In correlation with human-gait experience, the results also reveal some physical aspects favoring stability and the fact of switching between gaits to reduce the risk of falling in confronting different conditions.

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Cited by 1 Pith paper

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  1. Robust Push Recovery on Bipedal Robots: Leveraging Multi-Domain Hybrid Systems with Reduced-Order Model Predictive Control

    cs.RO 2025-04 conditional novelty 5.0 of 10

    A unified MPC using an augmented LIP model with ZMP dynamics enables a simulated Cassie biped to recover from large frontal and lateral pushes by simultaneously adjusting foot placement, step timing, and ankle effort.

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