Trajectory-Based Skill Learning Using Generalized Cylinders.
Trajectory-Based Skill Learning Using Generalized Cylinders.
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DOI：
10.3389/frobt.2018.00132
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发表时间：
2018
影响因子：
3.4
通讯作者：
Chernova S
中科院分区：
文献类型：
--
作者：
Ahmadzadeh SR;Chernova S
在本文中，我们介绍了一种新的基于轨迹的技能学习方法--广义圆柱体轨迹学习方法。为了模拟演示的技能，TLGC使用通用圆柱体-一种由称为脊椎的任意空间曲线和具有平滑变化的横截面的曲面组成的几何表示。我们的方法是第一次将广义圆柱体应用到操作中，其几何表示提供了几个关键特征：它通过对演示空间进行编码来识别和提取技能的隐含特征和边界，它支持生成保持这些特征的多个技能复制，所构建的模型可以通过轨迹编辑技术将技能推广到不可预见的情况，我们的方法还允许通过动觉校正来避开障碍和对所得到的模型进行交互式的人类改进。我们通过Jaco 6自由度和Sawyer 7自由度机械臂的一系列真实世界实验来验证我们的方法。
In this article, we introduce Trajectory Learning using Generalized Cylinders (TLGC), a novel trajectory-based skill learning approach from human demonstrations. To model a demonstrated skill, TLGC uses a Generalized Cylinder—a geometric representation composed of an arbitrary space curve called the spine and a surface with smoothly varying cross-sections. Our approach is the first application of Generalized Cylinders to manipulation, and its geometric representation offers several key features: it identifies and extracts the implicit characteristics and boundaries of the skill by encoding the demonstration space, it supports for generation of multiple skill reproductions maintaining those characteristics, the constructed model can generalize the skill to unforeseen situations through trajectory editing techniques, our approach also allows for obstacle avoidance and interactive human refinement of the resulting model through kinesthetic correction. We validate our approach through a set of real-world experiments with both a Jaco 6-DOF and a Sawyer 7-DOF robotic arm.