Efficient Humanoid Motion Planning on Uneven Terrain Using Paired Forward-Inverse Dynamic Reachability Maps
Efficient Humanoid Motion Planning on Uneven Terrain Using Paired Forward-Inverse Dynamic Reachability Maps
复制标题
使用成对的正向-反向动态可达性图在不平坦地形上进行高效的人形运动规划
DOI：
10.1109/lra.2017.2727538
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发表时间：
2017
影响因子：
5.2
通讯作者：
S. Vijayakumar
中科院分区：
文献类型：
--
作者：
Yiming Yang;W. Merkt;Henrique Ferrolho;V. Ivan;S. Vijayakumar
拟人机器人在复杂环境中规划操纵和运动的关键前提是找到具有可行的姿态位置和平衡无碰撞的全身构型的有效末端位姿。先前基于逆动态可达性图的工作假设脚在水平面上围绕站立位置相邻放置，成功率与采样空间的覆盖密度相关，而采样空间的覆盖密度又受到存储地图所需内存的限制。在这封信中，我们提出了一个框架，该框架使用成对的正逆动态可达性映射来利用机器人固有运动学结构的更大模块化。这种新型分解的组合允许在高维配置空间中更大的覆盖范围，同时减少存储样本的数量。这允许从更丰富的数据集中绘制样本，以有效地规划不平坦地形上的单手和手动任务的结束姿势。在38自由度NASA Valkyrie类人机器人上，利用全身冗余完成不平坦地形的避障操作任务，验证了该方法的有效性。
A key prerequisite for planning manipulation together with locomotion of humanoids in complex environments is to find a valid end-pose with a feasible stance location and a full-body configuration that is balanced and collision-free. Prior work based on the inverse dynamic reachability map assumed that the feet are placed next to each other around the stance location on a horizontal plane, and the success rate was correlated with the coverage density of the sampled space, which in turn is limited by the memory required for storing the map. In this letter, we present a framework that uses a paired forward-inverse dynamic reachability map to exploit a greater modularity of the robot's inherent kinematic structure. The combinatorics of this novel decomposition allows greater coverage in the high-dimensional configuration space while reducing the number of stored samples. This permits drawing samples from a much richer dataset to effectively plan end-poses for both single-handed and bimanual tasks on uneven terrains. This novel method was demonstrated on the 38-DoF NASA Valkyrie humanoid by utilizing and exploiting whole body redundancy for accomplishing manipulation tasks on uneven terrains while avoiding obstacles.