学习双足行走的推力恢复策略

Anais Estendidos do XIII Simpósio Brasileiro de Robótica e XVIII Simpósio Latino Americano de Robótica (SBR/LARS Estendido 2021) Pub Date : 2021-10-14 DOI:10.5753/wtdr_ctdr.2021.18686

D. C. Melo, M. Maximo, Adilson Marques da Cunha

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引用次数: 2

摘要

本工作提供了一种辅助仿人机器人行走引擎的推恢复控制器的实现。模拟环境是Robocup足球3D模拟联赛。学习的运动策略超过了我们原来的步行引擎。此外，我们评估了政策并发现了不希望出现的偏差。为了消除它，引入了新的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Learning Push Recovery Strategies for Bipedal Walking

The present work provides an implementation of a Push Recovery controller that aids the walking engine used by a humanoid simulated robot. The simulation environment is the Robocup Soccer 3D Simulation League. The learned movement policies exceeded our original walking engine. In addition, we evaluated the policies and detected undesired biases. New methodologies were introduced in order to eliminate it.

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来源期刊

Anais Estendidos do XIII Simpósio Brasileiro de Robótica e XVIII Simpósio Latino Americano de Robótica (SBR/LARS Estendido 2021)

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