Humans are highly adept at walking in environments with foot placement constraints, including stepping‐stone scenarios where footstep locations are fully constrained. Finding good solutions to stepping‐stone locomotion is a longstanding and fundamental challenge for animation and robotics. We present fully learned solutions to this difficult problem using reinforcement learning. We demonstrate the importance of a curriculum for efficient learning and evaluate four possible curriculum choices compared to a non‐curriculum baseline. Results are presented for a simulated humanoid, a realistic bipedal robot simulation and a monster character, in each case producing robust, plausible motions for challenging stepping stone sequences and terrains.

中文翻译：

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ALLSTEPS：课程驱动的垫脚石技能学习

人类非常擅长在脚部放置受限的环境中行走，包括足迹位置完全受限的踏脚石场景。为踏脚石运动寻找好的解决方案是动画和机器人技术的长期和根本性挑战。我们使用强化学习为这个难题提供了完全学习的解决方案。我们展示了课程对于有效学习的重要性，并与非课程基线相比评估了四种可能的课程选择。结果显示为模拟人形、逼真的双足机器人模拟和怪物角色，在每种情况下都会产生稳健、合理的运动，以挑战踏脚石序列和地形。