Towards a Simulator for Imitation Learning with Kinesthetic Bootstrapping
Towards a Simulator for Imitation Learning with Kinesthetic Bootstrapping
复制标题
走向具有动觉引导的模仿学习模拟器
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
B. Jung
中科院分区：
文献类型：
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作者：
Erik Berger;H. B. Amor;David Vogt;B. Jung
本文提出了一种基于物理的模拟器，它允许记录人和机器人之间的动觉交互，并随后用于模仿学习。我们认为，如果得到模拟引擎的适当支持，动觉交互可以成为机器人编程的一个非常重要的工具。为此，我们提出了一种新的基于动觉自举的机器人运动学习方案。与机器人的互动被用来创建一个低维的姿势空间。姿态空间与所呈现的模拟引擎一起允许快速模仿学习行为。使用遗传算法作为学习技术的这种方法的早期结果将被公布。
This paper presents a physics based simulator that allows kinesthetic interactions between a human and a robot to be recorded, and later used for imitation learning. We argue that kinesthetic interac- tion can be a very important tool for programming robots, if properly supported by a simulation engine. For this, we propose a new scheme for robot motion learning based on kinesthetic bootstrapping. Interactions with the robot are used to create a low-dimensional posture space. The posture space together with the presented simulation engine allow for fast imitation learning of behaviors. Early results of this approach, using Genetic Algorithms as learning technique, will be presented.