敏捷四足机器人运动技能切换准则的发现
Discovery of skill switching criteria for learning agile quadruped locomotion
AI总结：
针对四足机器人敏捷运动问题，提出分层学习与优化框架，通过深度强化学习与优化过程学习多技能策略，实现技能自动切换、故障恢复及平滑过渡，在模拟与现实中验证了效果。
摘要：
本文提出一种分层学习与优化框架，可学习并实现协调良好的多技能运动。所学习的多技能策略能在跟踪任意位置目标时自动、自然地切换技能，并迅速从故障中恢复。该框架包含深度强化学习与优化过程：首先，将接触模式融入奖励项，无需其他参考即可学习不同步态作为独立策略；其次，学习高层策略生成各策略权重，在目标跟踪任务中合成多技能运动，技能根据与目标的距离自动自然切换。在模拟Unitree A1机器人上验证了综合任务中的多技能运动，并在现实世界部署策略，实现小跑、跳跃、飞奔及其自然过渡，且能从意外故障中迅速恢复。相比现实中无法过渡到飞奔的单技能离散切换方法，该方法实现所有敏捷技能，且技能过渡更平滑连续。
英文摘要：
This paper develops a hierarchical learning and optimization framework that can learn and achieve well-coordinated multi-skill locomotion. The learned multi-skill policy can switch between skills automatically and naturally in tracking arbitrarily positioned goals and recover from failures promptly. The proposed framework is composed of a deep reinforcement learning process and an optimization process. First, the contact pattern is incorporated into the reward terms for learning different types of gaits as separate policies without the need for any other references. Then, a higher level policy is learned to generate weights for individual policies to compose multi-skill locomotion in a goal-tracking task setting. Skills are automatically and naturally switched according to the distance to the goal. The proper distances for skill switching are incorporated in reward calculation for learning the high level policy and updated by an outer optimization loop as learning progresses. We first demonstrated successful multi-skill locomotion in comprehensive tasks on a simulated Unitree A1 quadruped robot. We also deployed the learned policy in the real world showcasing trotting, bounding, galloping, and their natural transitions as the goal position changes. Moreover, the learned policy can react to unexpected failures at any time, perform prompt recovery, and resume locomotion successfully. Compared to discrete switch between single skills which failed to transition to galloping in the real world, our proposed approach achieves all the learned agile skills, with smoother and more continuous skill transitions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
