让四足机器人学会从零开始骑上移动滑板，突破传统训练瓶颈。
Quadrupedal Robot Skateboard Mounting via Reverse Curriculum Learning
- 从完成阶段反向训练，逐步增加任务难度
- 在固定滑板上学会后，成功迁移到移动滑板场景
- 适合对机器人控制与强化学习感兴趣的开发者
本工作旨在通过逆序课程强化学习，使四足机器人能够自主完成滑板骑行的登板过程。尽管已有研究实现了机器人已在滑板上的滑行能力，但初始登板阶段仍面临重大挑战。采用目标导向方法，从任务末端开始，逐步增加问题复杂度以逼近最终目标。训练初期将滑板固定在全局坐标系中，机器人位于其正上方；随后逐步放松初始条件，所学策略展现出对滑板位置和朝向变化的鲁棒性，最终成功迁移至动态滑板场景。代码、训练模型及可复现示例已公开于 https://github.com/dancher00/quadruped-skateboard-mounting。
原文摘要 · Abstract (English)
The aim of this work is to enable quadrupedal robots to mount skateboards using Reverse Curriculum Reinforcement Learning. Although prior work has demonstrated skateboarding for quadrupeds that are already positioned on the board, the initial mounting phase still poses a significant challenge. A goal-oriented methodology was adopted, beginning with the terminal phases of the task and progressively increasing the complexity of the problem definition to approximate the desired objective. The learning process was initiated with the skateboard rigidly fixed within the global coordinate frame and the robot positioned directly above it. Through gradual relaxation of these initial conditions, the learned policy demonstrated robustness to variations in skateboard position and orientation, ultimately exhibiting a successful transfer to scenarios involving a mobile skateboard. The code, trained models, and reproducible examples are available at the following link: https://github.com/dancher00/quadruped-skateboard-mounting
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