A Single-Planner Approach to Multi-Modal Humanoid Mobility
A Single-Planner Approach to Multi-Modal Humanoid Mobility
复制标题
多模式人形移动的单一规划器方法
DOI：
10.1109/icra.2018.8461134
复制
发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Likhachev
中科院分区：
文献类型：
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作者：
Andrew Dornbush;Karthik Vijayakumar;Sameer Bardapurkar;Fahad Islam;M. Likhachev
在这项工作中，我们提出了一种规划人形移动性的方法。人形移动性是一个具有挑战性的问题，因为人形机器人的配置空间非常大，特别是当机器人能够执行多种类型的运动时。例如，人形机器人可能能够执行双足行走、爬行和攀爬等任务。我们的方法是在单个搜索过程中规划所有这些任务。这使得搜索能够推理出机器人在任意点的所有能力，并得出完整的解决方案，从而保证该计划是可行的。一个关键的观察是，我们通常可以将移动任务粗略地分解为一系列较小的任务，并将规划工作集中在更小的搜索空间上进行推理。为此，我们利用最近开发的自适应维度规划框架的结果，并将可用控制器的功能直接纳入规划过程。生成的规划器还可以与执行一起以交错的方式运行，从而大大减少空闲时间。
In this work, we present an approach to planning for humanoid mobility. Humanoid mobility is a challenging problem, as the configuration space for a humanoid robot is intractably large, especially if the robot is capable of performing many types of locomotion. For example, a humanoid robot may be able to perform such tasks as bipedal walking, crawling, and climbing. Our approach is to plan for all these tasks within a single search process. This allows the search to reason about all the capabilities of the robot at any point, and to derive the complete solution such that the plan is guaranteed to be feasible. A key observation is that we often can roughly decompose a mobility task into a sequence of smaller tasks, and focus planning efforts to reason over much smaller search spaces. To this end, we leverage the results of a recently developed framework for planning with adaptive dimensionality, and incorporate the capabilities of available controllers directly into the planning process. The resulting planner can also be run in an interleaved fashion alongside execution so that time spent idle is much reduced.