Pré-Publication, Document De Travail Année : 2025

A Data-driven Contact Estimation Method for Wheeled-Biped Robots

Résumé

Contact estimation is a key ability for limbed robots, where making and breaking contacts has a direct impact on state estimation and balance control. Existing approaches typically rely on gate-cycle priors or designated contact sensors. We design a contact estimator that is suitable for the emerging wheeled-biped robot types that do not have these features. To this end, we propose a Bayes filter in which update steps are learned from real-robot torque measurements while prediction steps rely on inertial measurements. We evaluate this approach in extensive real-robot and simulation experiments. Our method achieves better performance while being considerably more sample efficient than a comparable deep-learning baseline.
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Dates et versions

hal-04726386 , version 1 (16-10-2024)
hal-04726386 , version 2 (22-01-2025)

Identifiants

Citer

Ü. Bora Gökbakan, Frederike Dümbgen, Stéphane Caron. A Data-driven Contact Estimation Method for Wheeled-Biped Robots. 2025. ⟨hal-04726386v2⟩
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