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Titel:

Online Virtual Repellent Point Adaptation for Bipedal Walking usinng Iterative Learning Control

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Shengzhi Wang, George Mesesan, Johannes Englsberger, Dongheui Lee, Christian Ott
Abstract:
We propose an online learning framework to reduce the effect of model inaccuracies and improve the robustness of the Divergent Component of Motion (DCM)-based walking algorithm. This framework uses the iterative learning control (ILC) theory for learning an adjusted Virtual Repellent Point (VRP) reference trajectory based on the current VRP error. The learned VRP reference waypoints are saved in a memory buffer and used in the subsequent walking iteration. Based on the availability of force-torq...     »
Kongress- / Buchtitel:
Humanoids 2020
Jahr:
2021
WWW:
https://humanoids2020-ieee.ipostersessions.com/?s=49-15-11-63-4D-A7-AE-64-B2-2A-F9-33-5E-26-D5-75
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