Identifying ground-robot impedance to improve terrain adaptability in running robots

To date, running robots are still outperformed by animals, but their dynamic behaviour can be described by the same model. This coincidence means that biomechanical studies can reveal much about the adaptability and energy efficiency of walking mechanisms. In particular, animals adjust their leg stiffness to negotiate terrains with different stiffnesses to keep the total leg-ground stiffness constant. In this work, we aim to provide one method to identify ground-robot impedance so that control can be applied to emulate the aforementioned animal behaviour. Experimental results of the method are presented, showing well-differentiated estimations on four different types of terrain. Additionally, an analysis of the convergence time is presented and compared with the contact time of humans while running, indicating that the method is suitable for use at high speeds

Identifying ground-robot impedance to improve terrain adaptability in running robots

© The Author(s). To date, running robots are still outperformed by animals, but their dynamic behaviour can be described by the same model. This coincidence means that biomechanical studies can reveal much about the adaptability and energy efficiency of walking mechanisms. In particular, animals adjust their leg stiffness to negotiate terrains with different stiffnesses to keep the total leg-ground stiffness constant. In this work, we aim to provide one method to identify ground-robot impedance so that control can be applied to emulate the aforementioned animal behaviour. Experimental results of the method are presented, showing well-differentiated estimations on four different types of terrain. Additionally, an analysis of the convergence time is presented and compared with the contact time of humans while running, indicating that the method is suitable for use at high speeds.This work was partially funded by the Spanish National Plan for Research, Development and Innovation through grant DPI2013-40504-R. Mr. Juan Carlos Arevalo and Mr. Manuel Cestari would like to thank the Spanish National Research Council and the Spanish Ministry of Economy and Competitiveness for funding their PhD research.Peer Reviewe