Generalized Cylinders for Learning, Reproduction, Generalization, and Refinement of Robot Skills
Generalized Cylinders for Learning, Reproduction, Generalization, and Refinement of Robot Skills
复制标题
用于机器人技能学习、复制、泛化和细化的广义圆柱体
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Chernova
中科院分区：
文献类型：
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作者：
S. Ahmadzadeh;M. A. Rana;S. Chernova
本文提出了一种新的几何方法，从人类示范学习和再现基于几何的技能。我们的方法模型的技能作为一个广义的圆柱体，一个几何表示组成的任意空间曲线称为脊柱和一个平滑变化的横截面。虽然这个模型已被用来解决其他机器人问题，这是第一次应用广义机器人操作。我们的方法的优势是该模型的能力，以识别和提取的隐含特征的演示技能，支持再现多个轨迹，保持这些特征，泛化到新的情况下，通过非刚性注册，并通过动觉教学的结果模型的交互式人类细化。我们验证我们的方法，通过几个现实世界的实验与雅科6自由度机械臂。
This paper presents a novel geometric approach for learning and reproducing trajectory-based skills from human demonstrations. Our approach models a skill as a Generalized Cylinder, a geometric representation composed of an arbitrary space curve called spine and a smoothly varying cross-section. While this model has been utilized to solve other robotics problems, this is the first application of Generalized Cylinders to manipulation. The strengths of our approach are the model’s ability to identify and extract the implicit characteristics of the demonstrated skill, support for reproduction of multiple trajectories that maintain those characteristics, generalization to new situations through nonrigid registration, and interactive human refinement of the resulting model through kinesthetic teaching. We validate our approach through several real-world experiments with a Jaco 6-DOF robotic arm.