Generating manipulation trajectory using motion harmonics
Generating manipulation trajectory using motion harmonics
复制标题
使用运动谐波生成操纵轨迹
DOI：
10.1109/iros.2015.7354073
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Yu Sun
中科院分区：
文献类型：
--
作者：
Yongqiang Huang;Yu Sun
本文提出了一种新颖的操纵轨迹生成算法，该算法根据学习的运动谐波和用户定义的约束构建轨迹。该算法使用函数特征分析从演示的运动中学习运动谐波，然后使用运动谐波来计算与演示的运动相似且满足约束的最佳轨迹。该算法已在五个真实人体运动数据集上进行了测试，以获得运动谐波，然后为 NAO 机器人生成每个任务的运动。将生成的轨迹与使用抛物线混合方法的线性段以及开放运动规划库生成的轨迹进行比较。该方法还可以与运动规划器一起使用。
This paper presents a novel manipulation trajectory generating algorithm that constructs trajectories from learned motion harmonics and user defined constraints. The algorithm uses functional eigenanalysis to learn motion harmonics from demonstrated motions and then use the motion harmonics to compute the optimal trajectory that resembles the demonstrated motions and also satisfies the constraints. The algorithm has been tested on five real human motion data sets to obtain motion harmonics and then generate motions of each task for a NAO robot. The generated trajectories were compared with the trajectories generated using linear segment with parabolic blend approach and with the Open Motion Planning Library. The approach can also work with motion planners.