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Thinning and smoothing of randomly-sampled support transitions toward practical motion planning for humanoid robots

机译:稀疏和平滑的随机采样支持过渡到类人机器人的实际运动计划

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A motion planning method for humanoid robots in life environments is proposed based on a two-stage approach, where a sequence of double support postures to represent discrete milestones of the biped locomotion is planned first, and then, a time series of the whole body configuration to interpolate them. This paper discusses the first stage. RRT (Rapidly-explored Random Tree) is utilized for the planning. The main problem is how to modify the sequence of randomly sampled double support postures into practically acceptable one. Some post-processing techniques including thinning and smoothing are presented. A necessary condition of the series of milestones is that a pair of adjacent postures has to share one fixed supporting foot as the pivot. In order to thin out unnecessary milestones, bypass nodes are inserted and Dijkstra's method is applied. A computer simulation in which a humanoid robot travels in an environment with some pieces of furniture is demonstrated.
机译:提出了一种基于两阶段方法的拟人机器人运动计划方法,该方法首先规划一系列代表双足机器人运动的离散里程碑的双支撑姿势,然后规划整个人体配置的时间序列插值它们。本文讨论了第一阶段。 RRT(快速探索的随机树)用于规划。主要问题是如何将随机采样的双支撑姿势的顺序更改为实际可接受的姿势。介绍了一些后处​​理技术,包括细化和平滑处理。系列里程碑的必要条件是,一对相邻的姿势必须共享一个固定的支撑脚作为枢轴。为了消除不必要的里程碑,插入了旁路节点并应用了Dijkstra的方法。演示了一种计算机模拟,其中有人形机器人在带有一些家具的环境中行驶。

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