用隐式接触优化方法，实现蛇形机器人高效越障运动规划。
Optimal Trajectory Planning in a Vertically Undulating Snake Locomotion using Contact-implicit Optimization
- 基于微分包含的简化模型，隐式处理复杂接触问题。
- 仿真与实验验证了模型精度与运动规划有效性。
- 适合对机器人接触动力学与轨迹优化感兴趣的研究者。
接触丰富的任务，如蛇形机器人运动，为基于优化的轨迹与无循环接触规划提供了未开发但潜力巨大的机会。以往的控制研究多聚焦于模仿蛇类运动模式，或使用忽略交互复杂性的形状函数，或专注于与物质（如钻洞）的复杂交互。然而，介于两者之间、基于简单刚体动力学且能缓解蛇形机器人中接触与控制分配难题的建模与控制框架仍属空白。本文在以下方向作出实质性贡献：1）提出一种基于莫雷奥微分包含方法的降阶模型；2）验证模型准确性；3）通过实验进行验证。
原文摘要 · Abstract (English)
Contact-rich problems, such as snake robot locomotion, offer unexplored yet rich opportunities for optimization-based trajectory and acyclic contact planning. So far, a substantial body of control research has focused on emulating snake locomotion and replicating its distinctive movement patterns using shape functions that either ignore the complexity of interactions or focus on complex interactions with matter (e.g., burrowing movements). However, models and control frameworks that lie in between these two paradigms and are based on simple, fundamental rigid body dynamics, which alleviate the challenging contact and control allocation problems in snake locomotion, remain absent. This work makes meaningful contributions, substantiated by simulations and experiments, in the following directions: 1) introducing a reduced-order model based on Moreau's stepping-forward approach from differential inclusion mathematics, 2) verifying model accuracy, 3) experimental validation.
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