Adaptive Control for Human-Robot Skilltransfer: Trajectory Planning Based on Fluid Dynamics
Adaptive Control for Human-Robot Skilltransfer: Trajectory Planning Based on Fluid Dynamics
复制标题
人机技能转移的自适应控制：基于流体动力学的轨迹规划
DOI：
10.1109/robot.2007.363583
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
R. Bauernschmitt
中科院分区：
文献类型：
--
作者：
H. Mayer;I. Nagy;A. Knoll;E. Braun;R. Lange;R. Bauernschmitt
简单灵活的机器人编程的一种流行方法是通过演示进行学习。智能控制器从有经验的用户执行的几个示例中学习任务。之后，该任务可以适应新的、以前未知的环境。这种技术带来的一个特殊挑战是演示的泛化，以获得任务的通用描述。本文提出了解决该问题的新方法。该算法的主要部分利用了流体动力学中已知的原理。
A popular method for an easy and also flexible programming of robots is learning by demonstration. An intelligent controller learns a task from several examples carried out by an experienced user. Afterwards, the task can be adapted to new, formerly unknown environments. One particular challenge arising with this technique is generalization of demonstrations in order to get a generic description of the task. In this paper a new methodology for solving this problem is proposed. The main part of the algorithm exploits principles known from fluid dynamics.